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Abstract

BACKGROUND:

Genetic mutations, peritoneal metastasis and frequent development of chemoresistance worsen the prognosis of ovarian carcinoma.

OBJECTIVE:

The objective of the study is to determine mutations in cancer susceptibility genes in relation with chemotherapy response.

METHODS:

In this follow up descriptive study, 47 consenting female patients diagnosed with surface epithelial ovarian cancer were observed for six months after completion of chemotherapy to see the treatment response. For genetic analysis, the DNA extraction was done and the genomic regions of different exons of BRCA1/2, PALB2, CHEK2, BAP1, CTNNB1, HOXB13, and PIK3CA were amplified using gene specific primers followed by Sanger Sequencing.

RESULTS:

86.7% of the patients were sensitive to chemotherapy whereas 13.3% showed resistance. Genetic variants of BRCA1 in 7%, BRCA2 in 4.7%, PIK3CA in 9.3%, PALB2 in 7%, CHEK2 in 2.3%, BAP1 in 2.3%, and CTNNB1 in 2.3% of the patients were found. There was also a significant association between TNM stage and the treatment response ( $p<$ 0.01). Of the patients with no mutations, 90.9% showed chemosensitivity as opposed to 70% in mutations group.

CONCLUSION:

Our study exhibits the pivotal role of genetic analysis in predicting the treatment response and paving pathway for patient tailored targeted therapy in Pakistani population.

Keywords

Epithelial ovarian cancer BRCA1/2 somatic mutations chemotherapy prognosis

1. Introduction

Surface epithelial ovarian cancer (SEOC), is the most fatal gynecological malignancy, having rapidly increasing incidence and mortality. GLOBOCAN 2020 by the International Agency for Research on Cancer reported 313,959 (1.6%) new cases of ovarian carcinoma worldwide with 207,252 (2.1%) deaths per year [1]. In Pakistan, 4326 (2.4%) cases have been reported with 2946 (2.5%) deaths in 2020 with cumulative risk of having ovarian carcinoma is 0.55% [2]. The treatment of ovarian cancer is complex because of heterogeneity of tumor. The reason for heterogeneity is diverse histological subtypes of SEOC because of different cellular origin, diverse mutational spectrum, which leads to different prognosis for every patient [3]. Different molecular subtypes can be present within one histological type with different prognoses [4]. Late stage diagnosis with peritoneal metastasis and chemoresistance has worsened the prognosis and survival rate [5].

SEOC is thought to be related to an accumulation of genetic alterations that can lead to alterations in expression of various genes. Along with deleterious mutations in homologous recombination genes, other cancer susceptibility genes also play an important role in the magnitude of cancer risk which could be helpful in making decisions regarding treatment protocols according to the local clinical oncology practice guidelines [6]. There is an increasing demand, by both health care providers and patients, for genetic testing due to the perceived clinical and economic advantages of this approach. The panels of mutational analysis include various homologous recombination genes (BRCA1, BRCA2, BARD1, ATM, BRIP1, CHEK2, NBN, PALB2, MRE11A, RAD50, RAD51D, RD51C, and XRCC2) along with other cancer susceptibility genes. Genetic testing provides a detailed insight of SEOC risk and progression thus playing an important role in ovarian carcinogenesis [7, 8].

BRCA mutated breast and ovarian cancers are mostly sporadic. The large prospective study in the United Kingdom observed that germline BRCA mutations were seen in 12.4% women out of which 5.4% represents BRCA2 mutations while 7.4% were of BRCA1 type [9]. Various studies reported that 10% incidence of BRCA mutations were reported in absence of family history of ovarian and/or breast cancers. BRCA mutation had been reported in 60–70% cases with family history of breast and/or ovarian cancers [10, 11]. The recent study conducted in Pakistan had detected 18.2% pathogenic BRCA mutations in cases of family history [12]. BRCA1/2 has an important role as a biomarker for specific diagnostics as well as a predictor for therapy. Previous studies have validated that patients with BRCA-mutations are more sensitive to first line chemotherapy as well as these cases show promising response after treatment with PARPi (inhibitors of Poly ADP Ribose Polymerase) [13, 14]. Presently in Pakistan, treatment options to these patients are not based on surveillance data or recommended international guidelines. To date, there is no study conducted for cancer susceptibility and prognostic genes in patients of SEOC in Pakistan and molecular targets relating the treatment response in Pakistan are yet to be defined from scratch. This follow up study was conducted to address the mutational status of a set of genes related to SEOC that aims to better define treatment response and outcome thus minimizing the burden of morbidity and mortality. The objective of the study is to give insight about the mutations in a set of cancer susceptibility genes in platinum resistant and sensitive patients of primary SEOC which may help in future studies with larger number of patients in modifying treatment modalities.

2. Material and method

2.1 Study population and sample collection

This was a follow up descriptive study conducted in INMOL (Institute of Nuclear Medicine and Oncology), Jinnah Hospital, Services Institute of Medical Sciences and Mayo Hospital, Lahore, Pakistan. Clinico-pathological/laboratory work was carried out in the Department of Morbid Anatomy and Histopathology, while, molecular studies were carried out at the Department of Physiology and Cell Biology, University of Health Sciences, Lahore. After approval from the institutional Ethical Review Board, a written informed consent was taken from each patient recruited in this study (Ethical review letter no.: UHS/REG-19/ERC/2071, dated: 12 June, 2019). The study comprised of forty seven consenting female patients diagnosed for the first time with resectable surface epithelial ovarian cancer presenting at the above mentioned tertiary care hospitals of Lahore. Relevant demographic information, selective present and past medical history, family history was taken and recorded on predesigned proformas after taking informed written consent following code of ethics of the World Medical Association (Declaration of Helsinki). After making a complete clinicopathological and radiological evaluation, surgery followed by chemotherapy was planned by the oncologists. Immediately after surgical resection, a representative portion of the excised malignant ovarian tissue and adjacent healthy tissue for comparison (0.5–1 gm) was snapped frozen in liquid nitrogen separately and stored at $-$ 80 ${}^{\circ}$ C for genomic analysis. Rest of the tissue was processed for fixation in formalin for histological analysis. The patients were followed up for six months after completion of chemotherapy to see the response of treatment. During treatment 2 patients died whereas insufficient DNA amount was extracted from two samples. Finally, 43 patients were followed and observed for 6 months after treatment (Fig. 1) (Graphical abstract).

Figure 1.

Flow diagram for registration of study participants, use of screening methodology and frequency of genetic mutations in the studied population (During treatment 2 patients died whereas insufficient DNA amount was extracted from two samples. Finally, 43 patients were followed and observed for 6 months after treatment).

2.2 Clinical evaluation

Updated International Federation of Gynaecology and Obstetrics (FIGO) (Jan. 2014)/TNM staging was done for each enrolled patient to ascertain the extent of tumor and the treatment options. Pre-surgery serum CA-125 levels were determined through ELISA.

2.3 Histopathological analysis

Processing/grossing of the surgical specimens’ (unilateral or bilateral oophorectomy, salpingo-oophorectomy either by laparotomy or laparoscopically, subtotal resection or removal of tumor fragments and hysterectomy with salpingo-oophorectomy) was done according to College of American Pathologists (CAP) protocol. Representative sections were taken for routine tissue processing and Hematoxylin and Eosin (H & E) staining. Histopathological reporting of the tumor was done according to CAP guidelines.

2.4 DNA extraction

For genetic analysis, the frozen tissue samples (0.5–1 gm) were grounded into small pieces in liquid nitrogen by using tissue homogenizer. Tissue sample was suspended in chilled lysis buffer. Protease inhibitor cocktail was added to avoid proteolysis during tissue lysis. Vigorous vortexing and centrifugation at 14,000 rpm for one hour at 4 ${}^{\circ}$ C was done. The DNA extraction was done by, DNA extraction Thermo Fischer Lithuania kit (cat #K0881, #K0882). The DNA was analyzed from tumor and adjacent healthy tissue. Pure tumor was used for mutational studies and that no germline DNA (from blood) was tested. The genomic regions of different exons of BRCA1/2, PALB2, CHEK2, BAP1, CTNNB1, HOXB13, and PIK3CA were amplified from extracted DNA using gene specific primers under optimized conditions (see Supplementary Sheets 1 and 2). The amplified products after purification were subject to Sanger Sequencing to identify the genetic variants in the exonic regions.

2.5 Chemotherapy response

Table 1a
Descriptive characteristics of socio-demographic and clinical variables ( $N=$ 45)

Variables	$f$ (%)	M ( $\pm$ SD)
Age (years)		46.04 (11.71) years
$\leqslant$ 30	04 (8.9)
31–40	14 (31.1)
41–50	12 (26.7)
51–60	12 (26.7)
$\geqslant$ 61	03 (6.7)
Martial status		–
Never married	04 (8.9)
Ever married	41 (91.1)
Duration of illness (months)		5.0 (5.82) months
$<$ 5 months	29 (64.4)
$\geqslant$ 5 months	16 (35.6)
Parity		–
Infertile	12 (26.7)
Multiparous	33 (73.3)
Regular menstruation		–
No	11 (24.4)
Yes	34 (75.6)
CA125 levels at diagnosis	–	3510.96 (14595.91) U/L
CA125 levels post chemotherapy	–	263.49 (664.72) U/L
Difference in CA125 levels pre-& post chemotherapy		3247.47 (14393.44) U/L
Reduced	43 (95.6)
Increased	02 (4.4)
Histopathological diagnosis		–
Serous cyst adenocarcinoma	39 (86.7)
Mucinous cyst adenocarcinoma	03 (6.7)
Endometrioid	02 (4.4)
Clear cell carcinoma	01 (2.2)
Histological grade		–
Low	15 (33.3)
High	30 (66.7)
FIGO/TNM stage
I	18 (40.0)
II	06 (13.3)
III	13 (28.9)
IV	08 (17.8)

After initial resection, the patients were enrolled for standard first-line chemotherapy comprising of a Taxane with the addition of Carboplatin (Inj. Paclitaxel intravenous with carboplatin in combination at one time, 3 weekly for 08 cycles with dose of paclitaxel ranging from 135 to 175 mg/m ${}^{2}$ ). During chemotherapy, patients’ baseline laboratory profile including complete blood count and liver function tests were monitored regularly. Each patient was followed-up for six months from the first day of the cycle till completion of standard chemotherapy in order to observe the response of treatment. The response was categorized after six months as resistant or sensitive to chemotherapy with aid of CA-125 levels and radiological scans according to NCCN clinical practice guidelines [24].

2.6 Statistical analysis

The data was entered and analyzed using IBM SPSS (Statistical Package for Social Sciences) version 24. Mean $\pm$ SD was given for normally distributed quantitative variables (age, duration of illness, CA125 levels) and Median with IQR were given for non-normally distributed quantitative variables. Frequencies and percentages were given for categorical (marital status, menstrual irregularities) variables. A $p$ -value of $\leqslant$ 0.05 in two tails was considered statistically significant for all purposes. The association of socio-demographic and clinical variables with BRCA 1/2 and with outcome was analyzed using Fisher’s Exact analysis. Wilcoxon Signed Rank Test was applied to see the statistically significant median differences between CA125 levels at the time of diagnosis and after administration of chemotherapy.

3. Results

Table 1a shows socio-demographic and clinical variables of 45 patients in studies population. The mean age with standard deviation of the ovarian cancer patients in the study was 46.04 ( $\pm$ 11.71) years, with 53.4% of patients between the ages of 41–60 years. Out of these, 91.1% of the patients were ever-married, with 73.3% categorized as multiparous. Dysmenorrhea was reported by 75.6% of the patients. The mean duration of illness was 5.0 (5.82) months, with 64.4% of the patients reporting the duration as less than 5 months. Most of the patients (86.7%) were diagnosed with Serous Epithelial Ovarian Carcinoma; out of which 66.7% of the patients were categorized as having high grade tumors and 46.7% of the patients were in the 3 ${}^{\text{rd}}$ and 4 ${}^{\text{th}}$ stage of cancer. The mean CA125 levels at the time of diagnosis was 3510.96 (14595.91) U/L and the mean CA125 levels after the chemotherapy was 263.49 (664.72) U/L. The mean difference in CA125 levels pre- and post-treatment was 3247.47 (14393.44) U/L, with CA125 levels decreasing in 95.6% of the patients (Table 1a). While 43 cases showed decline in CA125 levels where as 2 cases showed higher levels of CA125 after chemotherapy (Fig. 2a and b). BRCA 1/2 genetic variants were found positive in 11.6% of the patients, with BRCA 1 positive in 7% and BRCA 2 positive in 4.7% of the patients. Other mutations were found in 23.3% of the patients, with PIK3CA in 9.3%, PALB2 in 7%, CHEK2 in 2.3%, BAP1 in 2.3%, and CTNNB1 in 2.3% of the patients. 86.7% of the patients were sensitive to chemotherapy whereas 13.3% were resistant (Table 1b).

Figure 2.

Serum levels of CA125 in response to chemotherapy. (a) CA125 levels pre-chemotherapy with respect tor treatment response. (b) CA125 levels post-chemotherapy with respect tor treatment response. (c) Median differences between CA125 levels at the time of diagnosis and after administration of chemotherapy.

Table 1b

Frequency of genetic mutations in the studied population ( $N=$ 43)

Variables	Freq. (%)
BRCA 1 ( $n=$ 43)
Negative	40 (93.0)
Positive	03 (7.0)
BRCA 2 ( $n=$ 43)
Negative	41 (95.3)
Positive	02 (4.7)
BRCA 1/2 ( $n=$ 43)
Negative	38 (88.4)
Positive	05 (11.6)
Other mutations ( $n=$ 43)
No	33 (76.7)
Yes	10 (23.3)
PIK3CA ( $n=$ 43)
Negative	39 (90.7)
Positive	04 (9.3)
PALB2 ( $n=$ 43)
Negative	40 (93.0)
Positive	03 (7.0)
CHEK2 ( $n=$ 43)		–
Negative	42 (97.7)
Positive	01 (2.3)
BAP1 ( $n=$ 43)		–
Negative	42 (97.7)
Positive	01 (2.3)
CTNNB1 ( $n=$ 43)		–
Negative	42 (97.7)
Positive	01 (2.3)
Outcome of chemotherapy		–
Resistance	06 (13.3)
Sensitive	39 (86.7)

Table 2

Cross tabulations of socio-demographic and clinical variables in the absence/presence of BRCA 1/2 mutations ( $n=$ 43)

Variable	BRCA 1/2		Fisher’s exact $p$ -value
	Negative $n$ (%)	Positive $n$ (%)
Age (years)			1.000
$\leqslant$ 45 ( $n=$ 23)	20 (87.0)	03 (13.0)
$\geqslant$ 46 ( $n=$ 20)	18 (90.0)	02 (10.0)
Martial status			1.000
Unmarried ( $n=$ 03)	03 (100)	–
Ever married ( $n=$ 40)	35 (87.5)	05 (12.5)
Duration of illiness (months)			0.643
$<$ 5 ( $n=$ 28)	24 (85.7)	04 (14.3)
$\geqslant$ 5 ( $n=$ 15)	14 (93.3)	01 (6.7)
Parity			0.306
Infertile ( $n=$ 11)	11 (100)	–
Multiparous ( $n=$ 32)	27 (84.4)	05 (15.6)
Regular menstruation			0.221
No ( $n=$ 11)	09 (81.8)	02 (18.2)
Yes ( $n=$ 32)	29 (90.6)	03 (9.4)
Difference in CA125 levels pre-post chemotherapy			0.221
Reduced ( $n=$ 41)	37 (90.2)	04 (9.8)
Increased ( $n=$ 02)	01 (50)	01 (50)
Histopathological diagnosis			0.547
Serous cyst adenocarcinoma ( $n=$ 37)	33 (89.2)	04 (10.8)
Mucinous cyst adenocarcinoma ( $n=$ 3)	02 (66.7)	01 (33.3)
Endometrioid ( $n=$ 2)	02 (100)	–
Clear cell carcinoma ( $n=$ 1)	01 (100)	–
Histological grade			0.643
Low ( $n=$ 15)	14 (93.3)	01 (6.7)
High ( $n=$ 28)	24 (85.7)	04 (14.3)
FIGO/TNM stage			0.702
I ( $n=$ 18)	16 (88.9)	02 (11.1)
II ( $n=$ 05)	05 (100)	–
III ( $n=$ 12)	11 (91.7)	01 (8.3)
IV ( $n=$ 08)	06 (75.0)	02 (25.0)
Other mutations			0.320
No ( $n=$ 33)	28 (84.8)	05 (15.2)
Yes ( $n=$ 10)	10 (100)	–
PIK3CA			1.000
Negative ( $n=$ 39)	34 (87.2)	05 (12.8)
Positive ( $n=$ 04)	04 (100)	–
PALB2			1.000
Negative ( $n=$ 40)	35 (87.5)	05 (12.5)
Positive ( $n=$ 03)	03 (100)	–
CHEK2			1.000
Negative ( $n=$ 42)	37 (88.1)	05 (11.9)
Positive ( $n=$ 01)	01 (100)	–
BAP1			1.000
Negative ( $n=$ 42)	37 (88.1)	05 (11.9)
Positive ( $n=$ 01)	01 (100)	–
CTNNB1			1.000
Negative ( $n=$ 42)	37 (88.1)	05 (11.9)
Positive ( $n=$ 01)	01 (100)	–

Table 2 shows the association of socio-demographic and clinical variables with BRCA 1/2 was analyzed using Fisher’s Exact analysis in 43 patients. The data shows that in patients whom CA125 levels decreased after chemotherapy, 9.8% were positive for BRCA 1/2 mutations, whereas a large number of patients (90.2%) were negative for BRCA 1/2 mutations. With respect to mutations present in patients, BRCA 1/2 was found positive in 15.2% of the patients and negative in 84.8% of the patients (Table 2).

Table 3a

Socio-demographic and clinical variables with outcome of chemotherapy ( $N=$ 45)

Variable	Outcome		Fisher’s exact $p$ -value
	Resistance $n$ (%)	Sensitive $n$ (%)
Age (years)			0.396
$\leqslant$ 45 ( $n=$ 24)	02 (8.3)	22 (91.7)
$\geqslant$ 46 ( $n=$ 21)	04 (19.0)	17 (81.0)
Martial status			1.000
Unmarried ( $n=$ 04)	–	04 (100)
Ever married ( $n=$ 41)	06 (14.6)	35 (85.4)
Duration of illiness (months)			1.000
$<$ 5 ( $n=$ 29)	04 (13.8)	25 (86.2)
$\geqslant$ 5 ( $n=$ 16)	02 (12.5)	14 (87.5)
Parity			1.000
Infertile ( $n=$ 12)	01 (8.3)	11 (91.7)
Multiparous ( $n=$ 33)	05 (15.2)	28 (84.8)
Regular menstruation			1.000
No ( $n=$ 11)	01 (9.1)	10 (90.9)
Yes ( $n=$ 34)	05 (14.7)	29 (85.3)
Difference in CA125 levels pre-post chemotherapy			0.015
Reduced ( $n=$ 43)	04 (9.3)	39 (90.7)
Increased ( $n=$ 02)	02 (100)	–
Histopathological diagnosis			1.000
Serous cyst adenocarcinoma ( $n=$ 39)	05 (12.8)	34 (87.2)
Mucinous cyst adenocarcinoma ( $n=$ 03)	–	03 (100)
Endometrioid ( $n=$ 02)	01 (50)	01 (50)
Clear cell carcinoma ( $n=$ 01)	–	01 (100)
Histological grade			0.647
Low ( $n=$ 15)	01 (6.7)	14 (93.3)
High ( $n=$ 30)	05 (16.7)	25 (83.3)
FIGO/TNM stage			0.003
I ( $n=$ 18)	–	18 (100)
II ( $n=$ 06)	01 (16.7)	05 (83.3)
III ( $n=$ 13)	01 (7.7)	12 (92.3)
IV ( $n=$ 08)	04 (50.0)	04 (50.0)
Other mutations			0.127
No ( $n=$ 33)	03 (9.1)	30 (90.9)
Yes ( $n=$ 10)	03 (30)	07 (70)

Table 3b

Association of the genetic mutations with outcome of chemotherapy ( $N=$ 43)

Genes	Outcome		Fisher’s exact $p$ -value
	Resistance $n$ (%)	Sensitive $n$ (%)
PALB2			0.370
Negative ( $n=$ 40)	05 (12.5)	35 (87.5)
Positive ( $n=$ 03)	01 (33.3)	02 (66.7)
CHEK2			1.000
Negative ( $n=$ 42)	06 (14.3)	36 (85.7)
Positive ( $n=$ 01)	–	01 (100)
BAP1			0.140
Negative ( $n=$ 42)	05 (11.9)	37 (88.1)
Positive ( $n=$ 01)	–	01 (100)
CTNNB1			1.000
Negative ( $n=$ 42)	06 (14.3)	36 (85.7)
Positive ( $n=$ 01)	–	01 (100)
BRCA1			0.370
Negative ( $n=$ 40)	05 (12.5)	35 (87.5)
Positive ( $n=$ 03)	01 (33.3)	02 (66.7)
BRCA2			0.262
Negative ( $n=$ 41)	05 (12.2)	36 (87.8)
Positive ( $n=$ 02)	01 (50.0)	01 (50.0)
BRCA1/2			0.135
Negative ( $n=$ 38)	04 (10.5)	34 (89.5)
Positive ( $n=$ 05)	02 (40.0)	03 (60.0)

Table 3a presents the cross tabulations of socio-demographic and clinical variables with chemotherapy response in 45 patients. The results further showed that there was a significant association between mean CA125 levels pre- and post-therapy ( $p<$ 0.05), with 90.7% of the patients having significantly reduced CA125 levels depicting sensitivity to the chemotherapy. There was also a significant association between the TNM stage and the response to chemotherapy ( $p<$ 0.01), with all patients in stage I and majority patients in stage II (83.3%) and stage III (92.3%) showing chemosensitivity. Table 3b shows cross tabulations of genetic mutations with outcome of chemotherapy. Of the patients with no mutations, 90.9% showed chemosensitivity as opposed to 70% in the mutations group. Of the patients with negative BRCA 1/2, 89.5% showed chemosensitivity as opposed to 60% with positive BRCA 1/2. Out of 3 cases of PALB2 mutations, one case was resistant while one case of BAP1 mutation shows chemoresistance.

Figure 3.

Chemotherapy response with presence/absence of BRCA1/2 mutations in the studied population.

The graphically represented results further showed in Fig. 2c that the median differences between CA125 levels at the time of diagnosis and after administration of chemotherapy, as analyzed through related samples using the Wilcoxon Signed Rank Test was statistically significant ( $p<$ 0.0001).

Figure 3 depicts the chemotherapy response with respect to BRCA1/2 mutations. The studied population showed 6 cases of chemoresistance while 39 cases of chemosensitive response. Out of 3 cases of BRCA1 mutation positive, one case (33.3%) was resistant to chemotherapy. While out of 2 cases of BRCA2 mutation positive, one case (50%) was resistant. So out of 5 BRCA 1/2 positive cases, only 2 were resistant while 3 were sensitive. Moreover, both the resistant cases were of stage IV.

Table 4 depicts the mutational analysis in individual cases alongwith response to chemotherapy in studied population. There was no single case that had more than one mutation.

Table 4

Mutational analysis of studied population with chemotherapy response

Patient ID

Mutations (genes)

Chemotherapy

response

Case 1

A3127G (PIK3CA)

Sensitive

Case 4

IVS4-2A

>

G c.135-2A

>

G (BRCA1)

Resistant

Case 7

c.2997-2A (PALB2)

Sensitive

Case 10

p.Tyr173Cys (BAP1)

Resistant

Case 11

No genetic yield

Case 13

A3140G (PIK3CA)

Resistant

Case 21

I157T (CHEK2)

Sensitive

Case 22

804delT c.685del (BRCA1)

Sensitive

Case 24

p.S33C (CTNNB1)

Sensitive

Case 25

G1633A (PIK3CA)

Sensitive

Case 32

c.3114-1G

>

A (PALB2)

Resistant

Case 33

c.310G

>

A p.Asp104Asn (BRCA2)

Resistant

Case 36

L598X c.1793T

>

G (BRCA1)

Sensitive

Case 41

No genetic yield

Case 42

c.2629delT (PALB2)

Sensitive

Case 44

G1624A (PIK3CA)

Sensitive

Case 45

8897insT c.8669dup (BRCA2)

Sensitive

4. Discussion

The current follow-up study was conducted to comprehend the clinicopathological features and mutations in cancer susceptibility genes in SEOC patients along with response to chemotherapy in Pakistan. To the authors’ knowledge, previously no follow up study was conducted for cancer susceptibility and prognostic genes in patients of SEOC in Pakistan in relation to treatment response. The molecular targets relating the treatment response in Pakistan are yet to be defined from scratch. So this current follow up study will give insight into the genomics of SEOC in order to improve treatment response through selectivity thus minimizing the burden of morbidity and mortality. The results of this study showed important clinical implications in SEOC patients which may help in predicting the response to standard treatment and early detection. The mean age reported in this study was 46.04 $\pm$ 11.71 years (Table 1a) which is in accordance to the previous studies conducted [15, 16, 17]. The highest % of the patients was reported in 3 ${}^{\text{rd}}$ to 4 ${}^{\text{th}}$ decade of life (31.1%). SEOC are roughly 90% of all malignant ovarian tumors. Most of the patients present as clinical challenge in gynecological oncology, as most of these patients are asymptomatic until they have advanced disease [15, 18]. This study showed similar results as in 64.4% of the cases, duration of illness was $<$ 5 months (Table 1a). The most common histological variant was SEOC (86.7%) followed by mucinous (6.7%) and endometrioid type (4.4%) (Table 1a). The NRG oncology/gynecologic oncology group study also reported high incidence of SEOC i.e., 85% of SEOC and 4% of endometrioid type [19]. Similar results have been reported by studies conducted in Shaukat Khanum Hospital Lahore and Armed Forces Institute of Pathology (AFIP) from Pakistan [15, 12]. Mucinous type of ovarian cancer had been reported in the ranges of 7%–12% by Irodi et al in a 35 years prospective study [20]. The current study has reported 40% of cases in stage I while 17.8% were of stage IV (Table 1a) and these findings are in consistent with the previous studies conducted in tertiary care units in Pakistan whereas a 35 years cohort study reported large number of cases (40%–50%) in stage III [12, 15, 20]. The reason of high number of patients with stage I tumor in the current study group could be because the current study is conducted in the leading tertiary care centers of Pakistan with adequate and advanced radiological and diagnostic facilities for the general public.

Serum CA125, a high molecular weight glycoprotein, is used for screening and monitoring for ovarian cancer recurrence along with physical examination and imaging techniques. Early detection of ovarian carcinoma can have a significant impact on survival rates. Rising levels of serum CA125 levels can predict about 80–90% of all recurrences [21]. In the current study, median differences between CA125 levels at the time of diagnosis and after chemotherapy were statistically significant (Fig. 2c); the declining levels were observed in 95.6% of cases while resistant cases showed an increasing trend in serum levels (Table 3a; Figs 2a and b). Previous studies have showed that disease progression and regression can be predicted in 90% of cases with variation in serum levels of CA125 [21, 22].

Chemotherapy along with cytoreductive surgery and platinum-based agents is the standard therapy for ovarian carcinoma. Initial response rate to this therapy can be as high as 65–80% but eventually half of these patients develop platinum resistance which can lead to an unfavorable prognosis [23]. In the current study the patients were followed for 6 months after first line of chemotherapy and it showed 86.7% of the patients were sensitive to first line chemotherapy with platinum based agents whereas 13.3% were resistant (Table 1b) according to NCCN guidelines [24]. There was also a significant association between tumor stage and the chemotherapy ( $p<$ 0.01) (Table 3a), with all patients in stage I and majority patients in stages II (83.3%) and III (92.3%) showing chemosensitivity (Table 3a). The study from Shaukat Khanum Hospital Lahore reported 33% recurrence in patients with ovarian carcinoma with a longer follow-up duration [15]. The success of treatment depends upon the early detection of ovarian cancer as in the present study 40% cases presented with stage 1 at the time of diagnosis. The most patients diagnosed with advanced stage of the disease presents with a high fatality-to-case ratio in ovarian carcinoma [25, 26].

American College of Obstetricians and Gynecologists (ACOG), NCCN and Society of Gynecologic Oncologists (SGO) suggests genetic testing and counseling for all epithelial ovarian carcinoma patients [27]. Different studies have shown that 10–15% of SEOC patients carry mutation in BRCA1 or BRCA2 [28, 11]. Similarly, in the current study BRCA 1&2 mutations were found in 11.6% of the patients, with BRCA 1 positive in 7% and BRCA 2 positive in 4.7% of all the patients (Table 1b). Copson et al. in the prospective study from United Kingdom on 2733 women reported that 12.4% of patients had germline BRCA mutations which includes 5.4% BRCA2 and 7.4% BRCA1 [9]. Rashid et al., had identified 26 hotspot mutations in BRCA1 and BRCA2 genes by Sanger sequencing in 523 breast cancer patients, out of which 84% of variants were detected in BRCA1 while 16% in BRCA2 [29]. Previous studies had reported 10% incidence of BRCA mutation in cases without family history of breast and/or ovarian cancers, while 60–70% of cases with family history of cancers had BRCA variant [10, 11]. This is in accordance to our study as the cases had no known family history of breast and/or ovarian cancers. In the present study, 80% of the cases with BRCA 1&2 mutations had high grade serous histology while 20% showed low grade (Table 2). Other studies have also shown high incidence of BRCA mutation in high grade serous subtypes. Wu et al. reported 30–40% incidence of BRCA mutation in high grade serous carcinoma patients while study from Pakistan by Tariq et al. reported 33.3% ( $n=$ 6) BRCA1 pathogenic variants in high grade serous variety [10, 12]. In the present study no BRCA mutation was detected in the endometrioid type which is in accordance to another study conducted in Pakistan [12]. A systematic review shows a lower probability ( $\sim$ 7.7%) of having germline BRCA mutation in endometrioid type ovarian cancer [30].

All the mutations identified in BRCA1 gene in the current study were pathogenic in nature i.e., IVS4-2A $>$ G (c.135-2A $>$ G), 804delT (c.685del) and L598X (c.1793T $>$ G). In-silico prediction software (SpliceSiteFinder, MaxEntScan, NNSPLICE, GeneSplicer, HumanSpliceFinder) predicts abolishment of the consensus splice site in IVS4-2A $>$ G (c.135-2A $>$ G) variant. Previous studies have shown this splice site variant in the BRCA1 gene which is expected to cause hereditary breast and ovarian cancer and is classified as pathogenic [31, 32] (Supplementary Sheet 2). In the current study this variant was present in patient with resistance to chemotherapy (Table 4).

In 804delT (c.685del) variant 1 nucleotide is deleted in exon 10 of the BRCA1 gene, creating a frameshift and premature translation stop signal resulting in an absent or non-functional protein product. Based on the available evidence, this variant is classified as pathogenic and has also been reported in the study conducted in India on breast/ovarian cancer patients [33, 34].

L598X c.1793T $>$ G this variant changes 1 nucleotide in exon 10 of the BRCA1 gene, creating a premature translation stop signal. This variant is expected to result in an absent or non-functional protein product and is classified as pathogenic [35, 36].

The variants reported in the current study for BRCA2 mutations were c.310C $>$ T (p.Asp104Asn) and c.8669dup. c.8669dup variant allele predicted to encode a truncated non-functional protein and is of pathogenic type. So far, only one submission for this variant has been done by Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) [37, 38]. In the current study c.310C $>$ T (p.Asp104Asn) variant was shown in patient with resistance to chemotherapy (Table 4).

A catalytic subunit of the class I phosphoinositide-3-kinases (PI3K) is being encoded by PIK3CA. The activation of the PI3K pathway has been linked with worst prognosis in SEOC [39]. The current study has shown 9.3% frequency of PIK3CA mutations (Table 1b) which is in accordance to the previous study which showed 2% to 12% mutations. PIK3CA mutations were a negative prognostic factor for survival in patients presenting with high-risk ovarian cancer requiring chemotherapy, possibly due to chemoresistance [40]. The present study documented 16.66% (one case showed mutation of PIK3CA out of 6 resistant cases) chemoresistance associated with PIK3CA (Table 3b). Response to neoadjuvant chemotherapy can be altered by activating PIK3CA mutations because of its potentially important role in chemoresistance, and a tumor free survival can be achieved [41].

For PIK3CA, the current study identified 4 variants, i.e., c.3127A $>$ C (p.Met1043Leu), c.3140A $>$ T (p.His1047Leu), c.1633G $>$ A (p.Glu545Lys), and c.1624 G $>$ A (p.Glu542Lys). In the present study c.3140A $>$ T (p.His1047Leu) variant was present in a patient with chemoresistance (Table 4). The c.1624G $>$ A (NM_006 218.4) variant in PIK3CA is a missense variant predicted to cause substitution of (p.Glu542Lys). c.1633G $>$ A (p.Glu545Lys) resulting in a conservative amino acid change located in the phosphoinositide 3-kinase, accessory (PIK) domain (IPR001263) of the encoded protein sequence. Numerous studies suggest that c.1633G $>$ A is a hot-spot mutation [42, 43, 44].

Partner and localizer of BRCA2 (PALB2) is a breast cancer susceptibility gene that plays an important role in DNA repair. Previous study from Pakistan has reported a novel nonsense mutation, p.Y743*, in one familial breast cancer patient (1/127, 0.8%). Besides, four in silico-predicted potentially functional mutations including three missense mutations and one 5’ untranslated region mutation were identified by Rashid et al [45]. In the present study we have identified 3 variants of PALB2 mutation i.e., c.2997-2A $>$ C, c.3114-1G $>$ A, c.2629delT. c.3114-1G $>$ A variant of PALB2 in the present study was present in a patient with chemoresistance. Similarly, c.3114-1G $>$ A and c.2629delT are germline PALB2 mutations which were high-risk mutations identified in previous study [46].

In the present study c.470T $>$ C (p.Ile157Thr) variant of CHEK2 was reported. In this variant isoleucine is being replaced with threonine at codon 157 (p.Ile157Thr) of CHEK2 protein. There is a moderate conservation of isoleucine residue along with moderate difference between isoleucine and threonine physicochemical activity. Individuals with this variant had a marginally increased risk of breast cancer [47].

A single c.98C $>$ G (p.Ser33Cys) variant was identified in the current study for CTNNB1. Chang et al. reported this variant as a hotspot for lineage diversity in cancer [48].

The BAP1 mutational variant c.519T $>$ C (p.Tyr173 Cys) is reported in the current study in a patient with chemo resistance to therapy. While this variant is classified previously as likely benign because of population frequency, RNA analysis, undamaged protein function, in silico models, lack of segregation with disease, along with co-occurrence, conservation of amino acids, absence of disease association in case-control studies, and/or the mechanism of disease or impacted region is not consistent with a recognized cause of pathogenicity [49].

HR deficiency was reported in approximately 50% of patients with high-grade serous ovarian cancer by The Cancer Genome Atlas (TCGA) [50]; but majority of patients were European, with only 3.2% of patients of Asian origin. Only few studies have been carried out to see the mutational profile of ovarian carcinoma in Asian countries. Choi et al. has reported 8.5% somatic BRCA mutations without germline mutations in a study on tissue samples from 77 Korean patients. They have suggested that more candidates for PARP inhibitor treatment can be identified by genomic analysis especially of somatic BRCA gene variants [51].

You et al. has reported 4.1% prevalence of somatic BRCA1/2 mutations in 172 Chinese women [52], similarly Zhao et al. reported prevalence 4.0% (in two patients out of fifty) [53] and Li et al. has reported somatic BRCA1/2 in four patients out of 62 (6.4%) [54] which are in accordance to the current study.

Presently in Pakistan treatment options to these patients are not based on surveillance data or recommended international guidelines so this study may give an insight into the genomics of SEOC in order to improve treatment response. In Pakistan, healthcare providers, gynecologists, still have greatly different opinions and suggestions about genetic testing for gynecologic oncology, and these ideas are also significantly different from the requirements and recommendations in the guidelines and consensus statements. The high cost of genetic testing is also an important barrier in Pakistan [55]. No patients in our study had ever utilized PARPi as its not in use despite long term survival in patients with BRCA1/2 mutations is documented in literature [56].

In conclusion the current study has shown that the mutational analysis can help to predict the treatment response in SEOC patients. Our data suggest that mutational status of cancer susceptibility genes should be incorporated as a criterion for genetic testing in Pakistan. Identification of individuals with mutations in cancer susceptibility genes will enable physicians to optimize cancer management. So considering the high incidence of chemoresistance in ovarian carcinoma and its relation with genetic mutations in Pakistani population, the current study has tried to give an insight into the genetics of SEOC patients.

Limitation of study

As it is a follow up study so there is a limitation of sample size and we have followed up the cases for 6 months after first line of chemotherapy so further studies may be conducted on a longer follow up and with larger number of patients to explore an in-depth relation between chemoresistance and survival rate in relation with genetic mutations occurring in our female population. Moreover, a portion/section of tumor was analyzed so it can not represent the full picture of the genetic alterations/heterogenicity of the tumor.

Authors contribution

Conception: Saba Khaliq, Nadia Naseem.

Interpretation or analysis of data: Atika Masood, Rahat Sarfraz, Amira Shami, Saima Zaki, Nadia Naseem.

Preparation of the manuscript: Atika Masood, Rahat Sarfraz.

Revision for important intellectual content: Saba Khaliq, Nadia Naseem.

Supervision: Saba Khaliq, Nadia Naseem.

Footnotes

Conflict of interest

None.

References

Sung

Ferlay

Siegel

R.L.

Laversanne

Soerjomataram

Jemal

and Bray

, Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries, CA: a Cancer Journal for Clinicians 71 (2021), 209–249.

Pakistan source Globocon (2020), accessed 1 March 2022. Available from: https://gco.iarc.fr/today/data/factsheets/populations/586-pakistan-fact-sheets.pdf.

Dagogo-Jack

and Shaw

A.T.

, Tumour heterogeneity and resistance to cancer therapies, Nature Reviews Clinical Oncology 5 (2018), 81–94.

Lisowska

K.M.

Olbryt

Student

Kujawa

K.A.

Cortez

A.J.

Simek

Dansonka-Mieszkowska

Rzepecka

I.K.

Tudrej

and Kupryjańczyk

, Unsupervised analysis reveals two molecular subgroups of serous ovarian cancer with distinct gene expression profiles and survival, J Cancer Res Clin Oncol 142 (2016), 1239–1252.

Kim

Han

Kim

S.I.

Kim

H.S.

Kim

S.J.

and Song

Y.S.

, Tumor evolution and chemoresistance in ovarian cancer, NPJ PrécisOncol 2 (2018), 20.

Damia

and Broggini

, Platinum Resistance in Ovarian Cancer: Role of DNA Repair, Cancers 11 (2019), 119.

Moretta

Berthet

Bonadona

Caron

Cohen-Haguenauer

Colas

Corsini

Cusin

A.P.

Delnatte

and Dussart

, The French Genetic and Cancer Consortium guidelines for multigene panel analysis in hereditary breast and ovarian cancer predisposition, Bulletin du Cancer 105 (2018), 907–917.

Thompson

E.R.

Rowley

S.M.

McInerny

Devereux

Wong-Brown

M.W.

Trainer

A.H.

Mitchell

Scott

R.J.

James

P.A.

and Campbell

I.G.

, Panel testing for familial breast cancer: calibrating the tension between research and clinical care, J Clin Oncol 34 (2016), 1455–1459.

Copson

E.R.

Maishma

T.C.

Tapper

W.J.

Cutress

R.I.

Greville-Heygate

Altman

D.G.

Eccles

Gerty

Durcan

L.T.

Jones

and Evans

D.G.

, Germline BRCA mutation and outcome in young-onset breast cancer (POSH): a prospective cohort study, The Lancet Oncology 19 (2018), 169–80.

10.

Kong

Liu

Yin

Wen

Feng

and Lu

, The first nationwide multicenter prevalence study of germline BRCA1 and BRCA2 mutations in Chinese ovarian cancer patients, International Journal of Gynecologic Cancer 27 (2017).

11.

Manchana

Phoolcharoen

and Tantbirojn

, BRCA mutation in high grade epithelial ovarian cancers, Gynecologic Oncology Reports 29 (2019), 102–5.

12.

Tariq

Gul

Khadim

Ud-Din

Tipu

H.N.

Asif

and Ahmed

, Next Generation Sequencing-Based Germline Panel Testing for Breast and Ovarian Cancers in Pakistan, Asian Pacific Journal of Cancer Prevention 22 (2021), 719–24.

13.

Vidula

and Bardia

, Targeted therapy for metastatic triple negative breast cancer: the next frontier in precision oncology, Oncotarget 8 (2017), 106167.

14.

Taylor

K.N.

and Eskander

R.N.

, PARP inhibitors in epithelial ovarian cancer, Recent Pat Anticancer Drug Discov 13 (2018), 145–58.

15.

Ali

S.I.

Sayyed

R.H.

Akbar

S.A.

Abubakar

and Syed

A.A.

, Retrospective study of ovarian malignancy managed in surgical unit at Shaukat Khanum Memorial Cancer Hospital and Research Centre, Lahore, JPMA 71 (2021).

16.

Deng

Ren

Wang

Guo

Feng

and Chen

, Age is associated with prognosis in serous ovarian carcinoma, Journal of Ovarian Research 10 (2017), 1–9.

17.

Rasul

H.M.

Tahera

and Rashid

, Distribution Parity in Females with Epithelial Ovarian Tumours, Asian Journal of Multidisciplinary Studies 6 (2018).

18.

Puri

Chadha

and Panteu

A.K.

, Epidemiology of ovarian tumours in Northern India-A Tertiary Hospital based study, Indian J Com Family Med 4 (2018), 37–41.

19.

Norquist

B.M.

Brady

M.F.

Harrell

M.I.

Walsh

Lee

M.K.

Gulsuner

Bernards

S.S.

Casadei

Burger

R.A.

Tewari

K.S.

and Backes

, Mutations in homologous recombination genes and outcomes in ovarian carcinoma patients in GOG 218: an NRG oncology/gynecologic oncology group study, Clinical Cancer Research 24 (2018), 777–83.

20.

Irodi

Rye

Herbert

Churchman

Bartos

Mackean

Nussey

Herrington

C.S.

Gourley

and Hollis

R.L.

, Patterns of clinicopathological features and outcome in epithelial ovarian cancer patients: 35 years of prospectively collected data, BJOG: An International Journal of Obstetrics & Gynaecology 127 (2020), 1409–20.

21.

Marcus

C.S.

Maxwell

G.L.

Darcy

K.M.

Hamilton

C.A.

and McGuire

W.P.

, Current approaches and challenges in managing and monitoring treatment response in ovarian cancer, Journal of Cancer 5 (2014), 25.

22.

Charkhchi

Cybulski

Gronwald

Wong

F.O.

Narod

S.A.

and Akbari

M.R.

, CA125 and ovarian cancer: a comprehensive review, Cancers 12 (2020), 3730.

23.

Gao

Zhen

and Feng

, Systematic analysis of ovarian cancer platinum-resistance mechanisms via text mining, Journal of Ovarian Research 13 (2020), 1–6.

24.

Morgan

R.J.

Armstrong

D.K.

Alvarez

R.D.

Bakkum-Gamez

J.N.

Behbakht

Chen

L.M.

Copeland

Crispens

M.A.

DeRosa

Dorigo

and Gershenson

D.M.

, Ovarian cancer, version 1.2016, NCCN clinical practice guidelines in oncology, J Natl Compr Canc Netw 14 (2016), 1134–1163.

25.

Pokhriyal

Kumar

R.HariprasadL.

and Hariprasad

, Chemotherapy resistance in advanced ovarian cancer patients, Biomarkers in Cancer 11 (2019), 1179299X19860815.

26.

De La Franier

and Thompson

, Early stage detection and screening of ovarian cancer: A research opportunity and significant challenge for biosensor technology, Biosensors and Bioelectronics 135 (2019), 71–81.

27.

Modesitt

Pederson

H.J.

and Adkins

R.T.

, Practical Cancer Genetics and Genomics in Women’s Health, Clinical Obstetrics and Gynecology 62 (2019), 687–99.

28.

Alsop

Fereday

and Meldrum

, BRCA mutation frequency and patterns of treatment response in BRCA mutation–positive women with ovarian cancer: a report from the Australian Ovarian Cancer Study Group, J Clin Oncol 30 (2012), 2654.

29.

Rashid

M.U.

Muhammad

Bajwa

Faisal

Tahseen

Bermejo

J.L.

Amin

Loya

and Hamann

, High prevalence and predominance of BRCA1 germline mutations in Pakistani triple-negative breast cancer patients, BMC Cancer 16 (2016), 1–10.

30.

Arts-de Jong

de Bock

G.H.

van Asperen

C.J.

Mourits

M.J.

de Hullu

J.A.

and Kets

C.M.

, Germline BRCA1/2 mutation testing is indicated in every patient with epithelial ovarian cancer: a systematic review, European Journal of Cancer 61 (2016), 137–45.

31.

Clin var Genomic variation as it relates to human health, NM_007294.4(BRCA1):c.135-2A>G, accessed 6 March 2022. Available from: https://www.ncbi.nlm.nih.gov/clinvar/variation/125567/?oq=IVS4-2A%3EG+c.135-2A%3EG+NM_007294.4(BRCA1):c.135-2A%3EG&m=NM_007294.4(BRCA1):c.135-2A%3EG.

32.

Findlay

G.M.

Daza

R.M.

Martin

Zhang

M.D.

Leith

A.P.

Gasperini

Janizek

J.D.

Huang

Starita

L.M.

and Shendure

, Accurate classification of BRCA1 variants with saturation genome editing, Nature 562 (2018), 217–22.

33.

Clin var Genomic variation as it relates to human health, NM_007294.4(BRCA1):c.685del (p.Ser229fs), accessed 8 March 2022. Available from: https://www.ncbi.nlm.nih.gov/clinvar/variation/55666/?oq=804delT+c.685del&m=NM_007294.4(BRCA1):c.685del%20(p.Ser229fs).

34.

Singh

Thota

Singh

Padhi

Mohan

Deshwal

Sur

Ghosh

Agarwal

Sarin

and Ahmed

, Screening of over 1000 Indian patients with breast and/or ovarian cancer with a multi-gene panel: prevalence of BRCA1/2 and non-BRCA mutations, Breast Cancer Research and Treatment 170 (2018), 189–96.

35.

Clin var Genomic variation as it relates to human health, NM_007294.4(BRCA1):c.1793T>G (p.Leu598Ter), accessed 8 March 2022. Available from: https://www.ncbi.nlm.nih.gov/clinvar/variation/54352/?oq=L598X%5bVARNAME%5d+c.1793T%3EG&m=NM_007294.4(BRCA1):c.1793T%3EG%20(p.Leu598Ter).

36.

Ratajska

Krygier

Stukan

Kuźniacka

Koczkowska

Dudziak

Śniadecki

Dębniak

Wydra

Brozek

and Biernat

, Mutational analysis of BRCA1/2 in a group of 134 consecutive ovarian cancer patients. Novel and recurrent BRCA1/2 alterations detected by next generation sequencing, Journal of Applied Genetics 56 (2015), 193–8.

37.

Clin var Genomic variation as it relates to human health, NM_000059.4(BRCA2):c.8669dup (p.Thr2891fs), accessed 8 March 2022. Available from: https://www.ncbi.nlm.nih.gov/clinvar/variation/267103/?oq=%22NM_000059.4(BRCA2):c.8669dup%20(p.Thr2891fs)%22%5Bvarname%5D&m=NM_000059.4(BRCA2):c.8669dup%20(p.Thr2891fs).

38.

Clin var Genomic variation as it relates to human health, NM_000059.4(BRCA2):c.312C>T (p.Asp104=), accessed 8 March 2022. Available from: https://www.ncbi.nlm.nih.gov/clinvar/variation/483065/?new_evidence=false.

39.

Noorolyai

Shajari

Baghbani

Sadreddini

and Baradaran

, The relation between PI3K/AKT signalling pathway and cancer, Gene 698 (2019), 120–8.

40.

Carden

C.P.

Stewart

Thavasu

Kipps

Pope

Crespo

Miranda

Attard

Garrett

M.D.

Clarke

P.A.

and Workman

, The association of PI3 kinase signaling and chemoresistance in advanced ovarian cancer, Molecular Cancer Therapeutics 11 (2012), 1609–17.

41.

Gasparri

M.L.

Bardhi

Ruscito

Papadia

Farooqi

A.A.

Marchetti

Bogani

Ceccacci

Mueller

M.D.

and Panici

P.B.

, PI3K/AKT/mTOR pathway in ovarian cancer treatment: are we on the right track? GeburtshilfeFrauenheilkunde 77 (2017), 1095–1103.

42.

Clin var Genomic variation as it relates to human health, NM_006218.4(PIK3CA):c.1624G>A (p.Glu542Lys), accessed 8 March 2022. Available from: https://www.ncbi.nlm.nih.gov/clinvar/variation/31944/?oq=%22NM_006218.4(PIK3CA):c.1624G%3EA%20(p.Glu542Lys)%22%5Bvarname%5D&m=NM_006218.4(PIK3CA):c.1624G%3EA%20(p.Glu542Lys).

43.

Clin var Genomic variation as it relates to human health, NM_006218.4(PIK3CA):c.1633G>A (p.Glu545Lys), accessed 9 March 2022. Available from: https://www.ncbi.nlm.nih.gov/clinvar/variation/13655/?oq=%22NM_006218.4(PIK3CA):c.1633G%3EA%20(p.Glu545Lys)%22%5Bvarname%5D&m=NM_006218.4(PIK3CA):c.1633G%3EA%20(p.Glu545Lys).

44.

Clin var Genomic variation as it relates to human health, NM_006218.4(PIK3CA):c.3140A>T (p.His1047Leu), accessed 9 March 2022. Available from: https://www.ncbi.nlm.nih.gov/clinvar/variation/13653/?oq=%22NM_006218.4(PIK3CA):c.3140A%3ET%20(p.His1047Leu)%22%5Bvarname%5D&m=NM_006218.4(PIK3CA):c.3140A%3ET%20(p.His1047Leu)#id_second.

45.

Rashid

M.U.

Khan

F.A.

Muhammad

Loya

and Hamann

, Prevalence of PALB2 Germline mutations in early-onset and familial breast/ovarian Cancer patients from Pakistan, Cancer Research and Treatment: Official Journal of Korean Cancer Association 51 (2019), 992–1000.

46.

Z.Y.

Liu

Xie

Liu

Tang

Wang

Yang

and Ouyang

, Germline PALB2 mutations in cancers and its distinction from somatic PALB2 mutations in breast cancers, Frontiers in Genetics 11 (2020), 829.

47.

Clin var Genomic variation as it relates to human health, NM_007194.4(CHEK2):c.470T>C (p.Ile157Thr), accessed 10 March 2022. Available from: https://www.ncbi.nlm.nih.gov/clinvar/variation/5591/?oq=I157T%5bVARNAME%5d+NM_007194.4(CHEK2):c.470T%3EC%20(p.Ile157Thr)&m=NM_007194.4(CHEK2):c.470T%3EC%20(p.Ile157Thr).

48.

Chang

M.T.

Asthana

Gao

S.P.

Lee

B.H.

Chapman

J.S.

Kandoth

Gao

Socci ND

N.D.

Solit

D.B.

Olshen

A.B.

and Schultz

, Identifying recurrent mutations in cancer reveals widespread lineage diversity and mutational specificity, Nature Biotechnology 34 (2016), 155–63.

49.

Clin var Genomic variation as it relates to human health, NM_004656.4(BAP1):c.519T>C (p.Tyr173=), accessed 9 March 2022. Available from: https://www.ncbi.nlm.nih.gov/clinvar/variation/240061/?oq=%22NM_004656.4(BAP1):c.519T%3EC%20(p.Tyr173=)%22%5Bvarname%5D&m=NM_004656.4(BAP1):c.519T%3EC%20(p.Tyr173=).

50.

Cancer Genome Atlas Research Network, Integrated genomic analyses of ovarian carcinoma, Nature 474 (2011), 609–15.

51.

Choi

M.C.

Hwang

Kim

Jung

S.G.

Park

Joo

W.D.

Song

S.H.

Lee

Kim

T.H.

Kang

and An

H.J.

, Clinical impact of somatic variants in homologous recombination repair-related genes in ovarian high-grade serous carcinoma, Cancer Research and Treatment: Official Journal of Korean Cancer Association 52 (2020), 634.

52.

You

Wang

Gao

and Liang

, Germline and somatic BRCA1/2 mutations in 172 Chinese women with epithelial ovarian cancer, Frontiers in Oncology 10 (2020), 295.

53.

Zhao

Yang

Cao

and Shen

, Germline and somatic mutations in homologous recombination genes among Chinese ovarian cancer patients detected using next-generation sequencing, Journal of Gynecologic Oncology 28 (2017).

54.

Shao

Tan

Zhong

Guo

Wang

and Ye

, Germline and somatic mutations of multi-gene panel in Chinese patients with epithelial ovarian cancer: a prospective cohort study, Journal of Ovarian Research 12 (2019), 1–9.

55.

Sarwar

H.A.

Iftikhar

Azhar

Munawar

Hanif

M.R.

Bakar

M.A.

and Siddiqui

, Achieving Complete Radiological and Bio-Chemical Response as a Predictor of Long-Term Survival in Stage IV Epithelial Ovarian Cancer, Cureus 13 (2021).

56.

Hennessy

B.T.

Timms

K.M.

Carey

M.S.

Gutin

Meyer

L.A.

and Flake

D.D.

, Somatic mutations in BRCA1 and BRCA2 could expand the number of patients that benefit from poly (ADP ribose) polymerase inhibitors in ovarian cancer, Journal of Clinical Oncology 28 (2010), 3570.

Potential prognostic role of somatic mutations in a set of cancer susceptibility genes in ovarian carcinoma: A follow-up multicentric study from Pakistan

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

2. Material and method

2.1 Study population and sample collection

2.3 Histopathological analysis

2.4 DNA extraction

2.5 Chemotherapy response

Table 1a Descriptive characteristics of socio-demographic and clinical variables ( N = 45)

3. Results

Limitation of study

Authors contribution

Footnotes

Conflict of interest

References

Table 1a
Descriptive characteristics of socio-demographic and clinical variables ( $N=$ 45)