Journal of Oncology Translational Research

Ovarian Carcinoma (OC) is the most lethal gynaecological tumour. While other female pelvic tumours such as uterine cervical cancer display a spectacular
decline due to identification of early stages and precursors, the incidence and mortality of OC remains about the same for the past five decades. The main
reason for this is the late clinical diagnosis in the majority of cases and the lack of reliable tumor markers for early stage neoplasms. The most common OC
is the Ovarian Serous Carcinoma (OSC) characterized by its lack of symptoms during the early stages. Less common OC, Endometrioid Carcinoma (EOC)
, Clear Cell and Mucinous Carcinomas (CCC and MC) become symptomatic in earlier stages due to symptoms outside the ovaries (pelvic masses, vaginal
bleeding, infertility, abdominal pain). Our clinical-pathologic studies revealed that Stage I OC confined to the ovary(ies) are diagnosed in less than one third
of OSC while the overall less common EOC, CCC and MC represent the majority of Stage I OC. Patients with OSC are older on average, are more often BRCA
positive and may have a personal /family history of breast cancer. Patients with EOC, CCC and MC are younger on average, have histories of infertility and/or
hyperestrogenism (endometrial polyps, hyperplasia, leiomyomas).. Patients with atypical endometriosis are at risk to develop EOC and CCC. Early diagnosis for
the more aggressive OSC is occasionally made due to more frequent medical exams because of family history or previous breast cancer.
Our study of Prophylactic salpingo-oophorectomy specimens by histologic, morphometric and molecular biology methods identified precursor/precancerous
lesions in the ovarian and fallopian tube epithelium (tubo-ovarian dysplasia) adjacent to invasive cancer and in patients at risk for OC. These findings are
shedding light into early ovarian carcinogenesis and may have implications in the choice of strategies for this still mostly elusive cancer.

Breast cancer is the 2nd most common cancer in urban Indian population because of changes in lifestyle, better economic status. Thus it is imperative to
diagnose, treat and increase the survival of these women especially in low to middle income group countries like India. There are several biomarkers available
which are important and play a role in diagnosis, treatment and prognosis of breast lesions. Steroid markers like estrogen (ER) and progesterone (PR) are nuclear
markers which are important for treatment and prognosis. Overexpression of HER2/neu a cell membrane marker and Ki67 a proliferation marker are important
for treatment and prognosis. Metastatic markers like E-cadherin and vimentin which when decreased are associated with increased chances of metastasis. It is
also related to increased ER expression and tumor budding (TB). Other factors like increase in angiogenesis leads to bad prognosis which can be identified by
markers like CD34 and vascular endothelial growth factor (VEGF).
All the above markers can be studied by various methods like Fine Needle Aspiration Cytology (FNAC), Manual Liquid Based Cytology (MLBC), Cell Block (CB)
and histopatholgy sections. Each method have their advantages and limitations which will be highlighted in the study.

Cervical cancer is the second commonest cancer in India. Early detection of cervical cancer has significant improvement on patient survival, morbidity and also
decreases economic burden on treatment cost. Screening for cervical cancer with conventional Pap smear (CPS) is still widely used investigation in low resource
settings like India. In this study we are presenting CPS which includes non-neoplastic and neoplastic conditions. The non-neoplastic conditions like Candida,
Bacterial vaginosis, Trichomoniasis, koilocytic atypia and malignancy are correlated with histopathology and p16 Immunohistochemical (IHC) marker where ever
possible. The non-neoplastic inflammatory conditions cause disruption of the cervical microflora and discontinuity of cervical epithelium. This leads to increased
susceptibility for oncogenic HPV. When HPV enters cervical epithelium, it remains dormant for prolonged period. As it enters replication, the E6, E7 genes cause
inhibition of p53 and RB tumor suppressor genes respectively. This negative feedback of RB gene by E7 leads to increased expression of p16 (CDK inhibitor)
in infected cells. The increased p16 immunoreactivity in epithelium shows HPV infectivity, such lesions have greater tendency to upgrade itself to carcinoma.
Our study tries to substantiate the above principle of HPV infection leading to cancer with non-neoplastic conditions being cofactors. CPS is a good screening
technique even with its limitations like obscuring factors which can be overcome by biopsy and p16 marker study. Thus, women in developing countries can be
protected from precancerous and cancerous conditions of cervix by easy method like CPS.

Diagnosis of Breast lesion has leaped rapidly from Fine Needle Aspiration Cytology (FNAC) to molecular methods. In some institutes, the best possible cost
effective diagnosis is given, whereas in others, molecular studies are done to provide the diagnosis which influences the therapeutic and prognostic outlook.
Grading of cytological features on FNAC smear is useful in categorizing the breast lesions. One of the novel method is MMS (Modified Masood Scoring). This
when correlated with Modified Scarf- Bloom- Richardson scoring (BRS) on histopathology (HPE) will grade the breast lesion accurately in case of malignancy.
There are various methods studied to assess the metastatic potential of breast cancer and two of them are lympho vascular invasion (LVI) and tumor budding (TB).
ER (Estrogen receptor) serves dual roles in breast cancer by predicting favorable disease outcome and by facilitating tumor progression. Digital histopathology is
the one among the state-of-the-art method in tissue diagnosis. Deep Learning Algorithms (DLA) have emerged as a promising artificial intelligience (AI) solution
for Histopathological study. Convolution Neural Networks is a well know DLA in AI. Mostly used in lot of Medical Image analysis for the classification, detection
and segmentation of the cancerous tissues. Recently, AI based methods have emerged as a promising tools for the detection of tumor buds and other biomarkers.
Our study correlates MMS, BRS, lymph node invasion, ER status and tumour budding (conventional and automated methods) in assessing the prognosis of
breast cancer.

Introduction: Cervical cancer is the most frequent cancer among women in Senegal. However, there are few data concerning the HPV types inducing neoplasia
and cervical cancers and their prevalence, in the general population of Senegal
Aims: The aim of this study is to determine the prevalence of HPV infection in Senegalese women aged from 18 years and older.
Materials and Methods: A study was performed on 498 cervix samples collected from healthy women aged 18 and older in Dakar. 438 other samples were
collected from three other regions, Thiès, Saint Louis and Louga. The samples were screened for 21 HPV genotypes using an HPV type-specific E7 PCR beadbased
multiplex genotyping assay (TS-MPG) which is a laboratory-developed method for the detection of HPV.
Results: The prevalence for pHR/HR-HPV in the region of Dakar was 20.68%. HPV 52 (3.21%) was the most prevalent HPV type, followed by HPV 16 (3.01%)
and HPV 31 (3.01%). In the regions of Thiès, Louga and Saint Louis, the prevalence for pHR/HR-HPV was 29.19%, 23.15% and 20%, respectively
Conclusion: The study revealed the specificity of the HR-HPV prevalence in Dakar and other regions of Senegal. The patterns differ from the one observed in the
other regions of the world and raise the issue of the development of vaccination program in the country. Such a program should take into account the real HPV
prevalence for an effective protection of HPV-associated diseases.