1. Title of the proposed research project 

Identification of genetic predictors responsible for local failure in margin-negative OSCC patients in India.

2. Summary A structured summary should contain the following subheadings: Rationale/ gaps in existing knowledge, Novelty, Objectives, Methods, and Expected outcome.

Rationale/ gaps in existing knowledge-  Despite R0-surgical resection, 10-30% of the buccal mucosa squamous cell carcinoma (BMSCC) patients show relapse with treatment failure and death. Molecular characterization of BMSCC has been done but no specific investigation on molecular pathogenesis of margin area which could be the potential driver in this regard.  

Novelty – Molecular characterization will be done of morphologically normal yet genetically altered residual tumour cells in margin area, which may be missed in histopathological assessment. This finding will determine prognostic accuracy that will be superior to the clinico-pathological estimation.

Objectives – The driver genes at margin, responsible for oncogenesis in R0 resected patients, and the predictors for local failure will be identified.  

Methods – Next generation sequencing (NGS) of BMSCC tumor/adjacent margin and normal tissue will be done with extended panel comprising of all relevant genes. The analysed data will be aligned between with and without recurrence group to pin-point the possible variants. The identified variants will, subsequently, be cross-validated in recurrent patients at cell-free DNA level to get an idea of the disease burden.    

Expected outcome - The identified molecular markers in negative surgical margins of BMSCC might help in predicting relapse-prone patients, determining treatment management and potentially improve the prognosis.

3. Does it cover a priority area? If yes please select the most appropriate one from the list below:

Non-communicable disease: Cancer – breast, cervix, oral, lung

4. Area of research (Please tick one):

               Development research

5. Keywords: Six keywords separated by comma which best describe your project may be provided.

BMSCC, surgical resectiom, negative margin, recurrence, genetic variants, Next generation sequencing, India

6. Abbreviations: Only standard abbreviations should be used in the text. List of abbreviations maximum of ten may be given as a list.

OSCC - Oral squamous cell carcinoma

BMSCC - Buccal mucosa squamous cell carcinoma

NGS - Next generation sequencing

cfDNA – cell free DNA

LB – Liquid biopsy

7. Problem Statement

Oral cancer comprises of tumors of majorly three regions- oral cavity, oropharynx and larynx, whereas oral squamous cell carcinoma (OSCC) is the most commonly diagnosed histopathologic subtype (> 90%). India has the largest number of oral cancer cases and carries one third of the total global burden of oral cancer. In 2020, 135,929 oral cavity cancers were estimated in India which is expected to increase by around 26% in 2030 [1]. Therefore, oral cancer poses a major public health concern in India. Moreover, 60–80% of the cases are detected at the advanced stage [2], without any prior clinical evidence of pre-malignant lesion [3] like leukoplakia, erythroplakia, reducing the five year survival to 20% only [4].

Tobacco consumption in the form of smokeless tobacco, betel-quid chewing, alcohol, poor oral hygiene, nutrient-deficient diet are common risks of oral cancer. Region-specific socio-economic conditions play a vital role because of the lower income group, lack of knowledge, behavioral risk factors such as tobacco chewing and insufficient access to updated molecular diagnostic aids, resulting in a delay in reporting of the disease [2, 5-7]. In a recent report by Vivek Borse et al. 2020, the distribution of oral cancer across India has been demonstrated where it is found that eastern India has the highest % of oral cancer incidence. Moreover, the median age of the affected group is 40-69Y which is literally younger population. Hence, if detected at early stage, the chance of disease curing is the highest.

Buccal mucosa (BM, 57.5%) appears to be the most affected site, followed by tongue [24.2%; 8]. In case of BM carcinoma, locoregional recurrence (rate, 30-80%) poses the main cause of treatment failure [9 ]. Several predictive factors for such recurrence have been reported: positive surgical margin, invasion into surrounding area, spread to lymph node and extracapsular extension of tumor from the involved lymph node [9]. Complete surgical resection with tumor-free margin status is, perhaps, the most important prognostic factor for relapse-free survival, specifically for BMSCC [10-11]. Ironically, 10-30% of OSCC patients with histologically normal surgical margins show local recurrence [12], leading to treatment failure and patient death. Malignancy is achieved when cells acquire abnormal genetic variants. Therefore, the variants present in histologically normal margin are the potential major contributors in driving the relapse. Despite the identification of genetic alterations, those have not yet been used routinely in clinical practice in the risk assessment of surgical margin-negative cases in eastern India. Considering the BMSCC patient load in this specific locality, our aim is to identify and develop a gene signature that can accurately predict the BMSCC patients at a higher risk of disease recurrence.

8. Rationale of the study

Despite improved treatment options, recurrences/metastases or a second primary tumour frequently observed in many OSCC patients. Even after complete removal (R0 resection) with a histo-pathologically tumour-free surgical margin (R0), recurrence-free survival can not be guaranteed, thus affecting therapy planning [13]. Trunk or initiating driver variants initiate the development of primary cancer cells. Gradually, branching alterations induce sub-clonal evolution leading to local disease recurrence [14-15]. Hence, from the perspective of molecular pathogenesis, it appears that morphologically normal yet genetically altered residual tumour cells, which may be missed/unidentified in histopathological assessment, are the drivers in recurrence [16-18]. Thus, there is a need to identify the genetic predictors to stratify the patients prone to relapse after curative surgery. However, monitoring the residual disease is quite challenging because of difficulty in identifying low concentrations of circulating tumor cells and genetic factors that cancer cells secrete into the bloodstream. Here, liquid biopsy (LB) is an emerging diagnostic modality for the detection of residual tumor and eventually cancer surveillance [19-20]. 

Added value to the existing information-  

A few recent reports have identified the molecular characteristics of recurrence prone patients after R0 surgical [21-23]; however none from Indian context. Because of the genetic diversity, ethnic and geographic differences contribute largely in cancer incidence, prognosis, and treatment outcomes. Here, the potential of clinical genomics will be best utilized to determine treatment management. In the era of customized medicine, our effort to address the region-specific genomic diversity will overcome the existing barriers in research and health care delivery. We consider that the identification of the gene signature of recurrence prone patients after R0 surgical resection will improve the treatment management by the surgeons.

9. Hypothesis/ Research question

Up to 30% of OSCC patients with histo-pathologically tumor free surgical margins usually develop recurrence causing significant reduction in overall survival. Here, the genetic variants in the margin area could be the possible contributor, which needs to be identified. Hence, our goal is to derive a gene-signature based prediction of R0-resected patients to determine diagnostic and prognostic accuracy that will be superior to the clinico-pathological estimation.

Once identified, in the next step, their clinical relevance will be assessed in only recurrent patients. In such way, these markers will be considered crucial in stratifying the high risk patients in clinical setting, thus will improve the survival rates.

10. Study Objectives 

To reach the goal, four objectives are framed -

1.     Sample selection/collection - tumor/margin/adjacent normal and blood from surgically resected (with tumor-free margin) of BMSCC patients will be collected.

Tentative sample size/year – 25 cases in 1^st year

                                                30 cases in 2^nd year

                                                20 cases in 3^rd year (recurrent only) for LB

2.     Approach – Functional genomics at DNA level will be applied where NGS-based targeted sequencing with 1200 gene panel (see annexure I for list of genes) will be done with the complete set of samples (except blood) for each case followed by data analysis.

3.     Analytical aspect - The analysed data from recurrent cases will be aligned with non-recurrent ones to identify the predictor variant(s). Variants present in only recurrent cases (fulfilling statistical significance) will be pin-pointed.

4.     Validation and adoption in clinical setting – the identified variants will be cross-validated by liquid biopsy in recurrent patients (whether commonly observed at cfDNA level) and eventually those variants could be used as risk-predictor and treatment management by the surgeon.

Figure: Schematic representation of the stepwise approach to cover each objective of the proposed work.

11. Methodology: 

a. Study design - This is a prospective, multicentric, observational study to assess the genetic determinants of surgical margins in resected Oral Squamous Cell Carcinoma and predictors of local failure, and over all survival.

b. Study site - The site would primarily be Homi Bhabha Cancer Hospital and Research Centre, Muzaffarpur, Bihar.

c. Methods (e.g. PICO) :

Sample collection and extraction

Ø  Tissues from margin/tumor/normal area will be collected in RNA Later and stored in -80℃ until use.

Ø  On the day of extraction, remove the tissue from tube, keep it on kimwipes tissue to remove the RNA later.

Ø  Tissue will then be lysed in Lysing matrix (MP BIO) following the set protocol and will be proceeded to DNA/RNA extraction by using All Prep DNA-RNA extraction kit (Qiagen).

Ø  The extracted DNA and RNA will be quantified by Qubit fluorometer using specific reagents and the integrity will be assessed by Tapestation 4200.

Ø  If the quality and quantity both pass the threshold value, will be proceeded for hybrid capture-based library preparation.

Library preparation – All-in-one library kit with DNA and RNA both from each case will be used. The adapter ligation, indexing, size-exclusion based cleaning, hybridization with probes, final collection of hybridized fragments will be done following the set protocol.

Sequencing – Paired end sequencing will be done on Illumina platform. The quality check parameters will be considered of the sequenced data before going for analysis.

Analysis – Bioinformatic analysis with set pipeline will be done for variant calling.

				Enrolment and Consenting Treatment Naïve Operable Buccal Mucosa Cancer (GB Complex) Patients
		Analyze the genetic predictors of Local failure, regional/distant and overall survival

 

Figure: Schematic representation of the stepwise approach to cover each objective of the proposed work.

d. Sample size - As our molecular pathology and genomics lab is in the nascent stage of functioning, we would like to embark on the project in a phased manner. We initially would like to enroll 100 consecutive operable Buccal Cancers at our Centre. The assumption used for the disease failure in Oral Cancer was from Nair et al 2017, 39.6% at a median followup of 31 months. With type 1 error rate of 5 % and 80% power, and a study duration of 3 years (median followup of 30 months) with 10% attrition the estimate was 364 patients. We would be completing the said study in a phased manner by improving our capacity by the end of 1 year, initially by enrolling 100 subjects.

Tentative sample size/year – 25 cases in 1^st year      (25 x 3 = 75 samples)

                                                30 cases in 2^nd year     (30 x 3 = 90 samples)

                                                20 cases in 3^rd year (recurrent only) for LB

Inclusion/exclusion criteria for sample selection –

Inclusion

1.      Treatment Naïve, Histologically, biopsy proven Oral Squamous cell Carcinoma of the Buccal Mucosa, alveolus, retromolar trigone.

2.      Surgically resectable with R0 margins, across stages T1 -T4b.

3.      Specimen Closest Gross margins more than 5 mm mucosal/ soft tissue.

4.      Surgically treatable OSCC planned for treatment at any center of Tata Memorial Center.

Exclusion

1.      Previously treated for Head neck cancer/ Oral Cancer

2.      Tongue, floor of mouth, Hard palate subsite

3.      Specimen closest margins of gross <5 mm

4.      Unresctable Oral Squamous cell carcinoma or in cases where R0 resection not feasible

5.      Patients on any non-standard treatment protocol- or enrolled in other study effecting outcome

6.      Patients with known hereditary conditions with increased risk of Oral Squamous Cell Carcinoma

7.      Premalignant lesions/conditions, suspect malignancies, or carcinoma in-situ

e. Implementation strategy – The identified variants, after validation, can be utilized in clinical practice leading to better survival.

f. Statistical analysis

g. Ethical issues : Ethical clearance will be taken from institutional ethical clearance (IEC) committee.

12. Expected outcome/ Deliverables aligned with research question (up to 100 words):

It is now well established that the tumor evolution takes place through pre-malignancy stages where multiple genetic variations are accumulated in cells which support the cellular transformation. This, eventually, turns out to be the basis of personalised oncology where patients with same cancer type show distinct genotype and requires treatment strategy. Considering the high rate of incidence as well as mortality of OSCC cases, our attempt to identify new prognostic and predictive markers is still worth to investigate. This will help us to understand the tumor behavior and may lead to stratify the genetically high-risk group of patients and keep them under monitoring for the assessment of relapse. 

13. Future plan based on expected outcomes (up to 100 words):

By the application of massively parallel sequencing, we can expect to identify the driver variants in margin area which may act as a predictor of local failure in OSCC. The identified variants can be cross-validated in recurrent patients in bigger cohort in next phase of investigation at both tissue and blood level. This may, eventually, lead to developing a gene-signature panel comprising of a handful number genes which may gradually be commercialized as part of molecular diagnostic approach for the treatment of BMSCC exclusive patients.

14. Whether the study is going to generate new intellectual property Please provide details

        No.

15. Timelines with achievable targets: GANTT/ PERT chart to be included.

References:

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3.      Daniel E. Johnson. Head and neck squamous cell carcinoma. Nat Rev Dis Primers. 2020 Nov 26; 6(1): 92.

4.      Vivek Borse et al.  Oral cancer diagnosis and perspectives in India. Sensors International. 2020; 1: 100046.

5.      Khandekar SP, Bagdey PS, Tiwari RR. Oral cancer and some epidemiological factors: A hospital based study. Indian J Community Med. 2006;31:157–9. 

6.      Kumar S et al. Delay in presentation of oral cancer: A multifactor analytical study. Natl Med J India. 2001;14:13–7

7.      Asthana S, Patil RS, Labani S. Tobacco-related cancers in India: A review of incidence reported from population-based cancer registries. Indian J Med Paediatr Oncol. 2016;37:152–7. 

8.      Ramachandra NB. The Hierarchy of Oral Cancer in India. Int J Head and Neck Surg 2012;3(3):143-146.

9.      Wen-Yen Chiou  et al. Buccal mucosa carcinoma: surgical margin less than 3 mm, not 5 mm, predicts locoregional recurrence. Radiat Oncol. 2010 Sep 15;5:79.  

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12.   Leemans CR et al. Recurrence at the primary site in head and neck cancer and the significance of neck lymph node metastases as a prognostic factor. Cancer 1994, 73(1):187-190.

13.   Mitchell DA et al. Margins and survival in oral cancer. Br J Oral Maxillofac Surg. 2018; 56(9):820-829.

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15.   Tabor MP et al. Multiple head and neck tumors frequently originate from a single preneoplastic lesion. Am J Pathol. 2002;161(3):1051-1060.

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