Sir Peter MacCallum Department of Oncology - Theses
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ItemReal-world Management and Outcomes for Anaplastic Lymphoma Kinase (ALK)- rearranged Advanced Non-small Cell Lung Cancer and Impact of COVID-19 on Cancer Service Delivery( 2023-09)This thesis is divided into two parts. Part 1 - Real-world Management and Outcomes for Anaplastic Lymphoma Kinase (ALK)-rearranged Advanced Non-small Cell Lung Cancer (ALK+ aNSCLC) ALK-rearrangements are found in 4% of Non-small cell lung cancers (NSCLC). Although this condition remains incurable, survival appears to be improving over time, with a multitude of selective oral tyrosine kinase inhibitors (ALK-inhibitors) now available and with many patients receiving multiple lines of therapy. Whilst next-generation ALK-inhibitors are standard of care in the first line, how to best sequence available therapies beyond this remains unclear. This thesis examines outcomes for real-world patients with ALK+ aNSCLC, using cohorts from AURORA (Australia) and Flatiron health (United States). Key findings: median overall survival (mOS) of 84 months in the AURORA cohort (n=171) and 37 months in the Flatiron cohort (n=737). Positive prognostic factors: never-smoking history, treatment in an academic setting and initial early stage at diagnosis. Gender was not prognostic. Treatment patterns varied and changed over time. Initial treatment with 2nd generation ALK-inhibitor was associated with improved survival over chemotherapy; initial treatment with 1st generation ALK-inhibitor followed by 2nd generation ALK-inhibitor was associated with improved survival compared to initial chemotherapy followed by 1st generation ALK-inhibitor. These retrospective observational studies represent the largest for people with ALK+ aNSCLC in Australia (AURORA) and globally (Flatiron). Future research may focus on intensifying treatment for people with a smoking history. Further work is required to determine why treatment in a community setting correlated with poorer survival in the US. Identifying optimal treatment sequences will require larger contemporary patient databases; collaboration is required among research organisations and with pharmaceutical companies conducting post-marketing studies. Part 2 - Impact of COVID-19 on Cancer Service Delivery Amid the early stages of the COVID-19 pandemic, significant shifts in patient presentation and oncology health service provision for people with lung and other cancer-types were observed globally. This research aimed to obtain timely real-world data on how clinicians perceived alterations in cancer service delivery due to COVID-19. Surveys were distributed to oncology clinicians through international professional societies in 2020. Clinicians highlighted substantial changes in oncology services. In the early period (May-June 2020), 89% of clinicians reported altering their practice due to COVID-19; including being less likely to initiate and more likely to cease systemic therapy in palliative and curative settings. Telehealth use was rapidly expanded; many clinicians reported concerns that this may negatively impact patient outcomes. Clinicians reported seeing fewer new patients in clinic. In the later period (October-November 2020), clinicians reported more advanced disease presentations and a swing back towards pre-COVID practice. Clinicians’ reported concerns regarding potential negative impact on cancer-related outcomes are further substantiated by global reports of fewer cancer diagnoses across 2020 and modelling studies predicting increase cancer-related mortality and health-care costs due to such changes. For cancer-related outcomes to be optimised through future pandemic events, heath-systems and policy makers need to have implementable action plans to rapidly upscale mitigation strategies, such as public education campaigns, telehealth and hospital in the home.
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ItemDevelopment and Implementation of Robotic Colorectal Cancer Surgery( 2023-03)Robotic colorectal surgery is increasingly being used around the world, but its status in Australia has not been explored. Whilst retrospective studies and a few trials have demonstrated its feasibility and safety, there is limited research on the potential advantages of using a robotic platform for complex oncologic procedures, where the penetration of minimally invasive surgery remains anecdotal. In addition, current evidence on the costs of robotic colorectal surgery compared to conventional laparoscopic surgery is limited and potentially outdated. This thesis addresses these gaps by examining the adoption of robotic colorectal surgery in Australia, revealing a dramatic increase in its use, particularly in the private sector. It also confirms that the implementation of robotic surgery for complex cancer work, such as complete mesocolic excision for right-sided colon cancer and beyond total mesorectal excision surgery for advanced or recurrent pelvic malignancies, is feasible. This expands our limited understanding of how minimally invasive techniques can be applied to navigate complex oncological scenarios, providing valuable insights into the technical aspects involved. The thesis also sheds light on the costs associated with robotic colorectal surgery compared to a conventional laparoscopic approach. Whilst it highlights the increased total costs, it acknowledges the limitations of the current data in this evolving field. Ultimately, this work provides baseline data to inform future economic evaluations, which will be required to support the wider adoption of robotic colorectal surgery in the public sector.
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ItemA cell-based functional assay that accurately links genotype to phenotype in Familial HLH( 2023-04)Cytotoxic lymphocytes protect humans against viral pathogens and cancer by killing infected and transformed cells, through perforin-mediated mechanism. Mutations in perforin (PRF1) itself or in the secretory machinery responsible for its release (UNC13D, STX11, and STXBP2) are catastrophic, and lead to fatal immune dysregulation, an autosomal recessive disease called familial haemophagocytic lymphohistiocytosis (FHL). Traditionally, FHL has been associated with infant patients. However, it is now apparent that many patients remain disease-free for years, and then present with highly variable and often unexpected symptoms. They remain undiagnosed for a long time and, instead of receiving curative stem cell transplantation, they are treated symptomatically leading to high risk of severe neurological impairment, organ failure and/or death. While the pathogenicity of frame-shift/nonsense mutations is rarely in doubt, the effect of missense mutations on protein function can vary enormously. Yet, over the last two decades, the pathogenicity of missense mutations was almost invariably assumed, and invasive stem cell transplantation was considered without confirmed pathogenicity of mutations. Sadly, transplantation without genetically proven FHL results in a 20% increased mortality compared to patients with proven FHL. Therefore, early and accurate diagnosis of the disease is essential to determine the most appropriate treatment option. Due to the diversity of genetic causes of FHL, there was no test available to directly assess the effect of mutations on cytotoxic lymphocyte function, leading to delayed/erroneous diagnoses. To overcome this diagnostic problem, we have developed a simple, rapid, and robust method that takes advantage of the functional equivalence of the human and mouse orthologues of PRF1, UNC13D, STX11 and STXBP2 proteins. By knocking out endogenous mouse genes in CD8+ T cells and simultaneously expressing their mutated human orthologues, we can accurately assess the effect of mutations on cell function. The wide dynamic range of this novel system allowed us to understand the basis of otherwise cryptic cases of FHL/HLH and, in some instances, to demonstrate that previously reported mutations are unlikely to cause FHL. In addition to diagnosing patients, this unique approach will be paramount for assessing the prognosis of asymptomatic siblings and to guide genetic counselling advice for prospective parents.
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ItemA Comprehensive Machine Learning System for Cancer Classification Experiments( 2023-01)Cancer detection, classification/subtyping, grading, segmentation and prognostication are promising applications of machine learning to oncology which, if successful, would yield substantial clinical benefits. Merely knowing a cancer’s subtype provides a clinician with deep insights into its nature and likely progress, effective treatments regimes, and the patient’s prognosis. The volume of studies which make use of machine learning in medicine, including in oncology, is large and growing. A variety of clinical aspirations are evident from the literature, including: improving patient outcomes by increasing cancer detection and classification accuracy; reducing cancer diagnosis costs, and reducing the time required to diagnose cancer. However, researchers wishing to incorporate machine learning into their research face a high barrier, since it requires specialised data science/machine learning skills over and above biomedical expertise. Further, few software tools are available to assist a researcher wishing to undertake such studies. Researchers typically develop necessary software themselves: a difficult and time consuming prerequisite activity to conducting experiments. In response to these shortcomings, I developed ‘CLASSI’: an experiment pipeline for cancer classification/subtyping using whole slide images or RNA-Seq gene expression data. CLASSI makes it straightforward for researchers to incorporate machine learning into their research for one important class of oncology experiments, viz.: cancer classification and subtyping using oncopathology images or RNA-Seq data. CLASSI advances the field by providing an ‘off-the-shelf’ experiment platform to simplify and automate the conduct of histopathology image and RNA-Seq data machine learning experiments, and demonstrates that ‘machine learning enabled’ experiment pipelines are feasible, supporting the case for the development of other, more broadly scoped, experiment pipelines.
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ItemOptimising cancer risk management for women at increased risk of breast cancer( 2022)Breast cancer is the most common cancer (after skin cancer) affecting women and is the second most common cause of cancer-related death for Australian women. Though breast cancer survival has improved in the last three decades, breast cancer incidence continues to rise and the disease now affects 1 in 7 women in their lifetime. In Australia, women are stratified into breast cancer risk categories (high, moderate or low) based on their lifetime risk of breast cancer. This categorisation helps guide a personalised approach to screening and breast cancer prevention with the aim of moving away from a “one size fits all” approach and towards precision prevention and screening based on personal risk level. This thesis aims to add to the personalised approach to management of breast cancer risk by: 1) contributing to a better understanding of barriers to effective risk management interventions that are currently available to women at elevated breast cancer risk and 2) reporting on the use of interventions offered to women that are not supported by evidence. Two studies presented in this thesis address the first aim. The first evaluates the current use of risk-reducing medication in Australia and the potential predictors of use. The second identifies barriers and facilitators to breast cancer risk-reducing medication from the perspectives of women and their clinicians. These studies demonstrate that the use of risk-reducing medication in Australia is very low, even compared to international standards. Novel barriers to risk-reducing medication use were identified, including women not having enough information to make a decision and clinicians being unaware of risk-reducing medications. The application of behavioural change theory to these results suggests the effective interventions to address these barriers would be: targeted education to clinicians and the public about the role and effectiveness of risk-reducing medications; campaigns to increase awareness of individualised breast cancer risk assessment; and policy change to facilitate routine breast cancer risk assessment. The second aim was addressed through two studies, the first evaluating the use of ineffective ovarian cancer screening in Australia and the second assessing the effectiveness of clinical breast examination as a component of breast cancer surveillance programs for women who carry a pathogenic variant in BRCA1 or BRCA2. The first study identified that ovarian cancer screening continues despite strong evidence and national guidelines not supporting its use. The facilitators of screening identified in this study included difficulty discontinuing screening, ordering screening tests for patient peace of mind and the lack of other available screening tests, highlighting the challenges of de-implementation of ineffective screening tests. Linking these identified facilitators with a validated behaviour change model pointed to interventions including education for clinicians and women on the ineffectiveness of ovarian cancer screening and a public campaign illustrating why high-profile women in the community do not screen for ovarian cancer. The second study demonstrated that clinical breast examination in carriers of a pathogenic variant in BRCA1 and BRCA2 has a very low clinical yield when used within a screening program that includes breast MRI, suggesting that clinical breast examination may be safely omitted in that setting. This thesis concludes that effective risk management interventions are underused in Australia, while there is continued widespread use of ineffective screening tests. Precision prevention for breast cancer requires the harnessing of available effective interventions and not offering tests that are not of benefit. Changes are required in our approach to breast cancer risk reduction to be successful in reducing breast cancer incidence in Australia.
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ItemAutomated discovery of interacting genomic events that impact cancer survival by using data mining and machine learning techniques( 2020)Rapid advancement in genomic technologies has driven down the cost of sequencing significantly. This efficiency has enabled large-scale cancer genomic studies to be conducted, generating a vast amount of data across different levels of omics variables. However, the tasks to extract new knowledge and information from this enormous volume of data present unique challenges. These analyses often require the application of specialised techniques for data mining, integration and interpretation to provide valuable insights. With the rise of machine learning adoption in recent decades, many advanced computational algorithms based on artificial intelligence techniques have also been proposed to analyse these genomics data. Although some of these applications have led to clinically relevant conclusions, many others are still relying on incomplete prior knowledge, or limited to only a selected number of features. These limitations raise the general question about the broader applicability of machine learning in the field of cancer genomics. This research addresses this question by assessing the application of machine learning techniques in the context of breast cancer genomics data. This assessment includes a comprehensive evaluation of computational methods for predicting cancer driver genes and the development of a novel deep learning approach for identifying breast cancer subtypes. The evaluation result of driver gene prediction algorithms suggests that the selection of the best method to be applied to a dataset will primarily be driven by the objectives of the study and the characteristics of the dataset. All of the evaluated approaches could identify well- studied genes, but not all of them performed as well on smaller datasets, subtype-specific cohorts, and in discovering novel genes. To examine the benefit of a more complex machine learning model, this thesis also presents a novel deep learning approach that integrates multi-omics data for predicting various breast cancer’ biomarkers and molecular subtypes. This method combines a semi-supervised autoencoder for dimensionality reduction, and a supervised multitask learning setup for the classifications. Taking an input of gene expression, somatic point mutation and copy number data, the algorithm predicts the ER-Status, HER2-Status and molecular subtypes of breast cancer samples. Further survival analysis of the outputs from this deep learning approach indicates that the predicted subtypes show a stronger correlation with patient prognosis compared to the original PAM50 label. While the outputs from machine learning algorithms still require further validation, the adoption of these complex computational methods in cancer genomics will become increasingly common. Collectively, the results from this thesis suggest that the machine learning analysis of ‘omics data hold great potential in automating the discovery of clinically- relevant molecular features.
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ItemInvestigating the mechanism of cytotoxic lymphocyte resistance to perforin( 2020)Cytotoxic lymphocytes are highly efficient killer cells of the immune system. They destroy cognate target cells by secreting highly toxic effector molecules, the pore-forming protein perforin and pro-apoptotic serine proteases granzymes, into the confines of the immune synapse. Despite both the lymphocyte and target cell plasma membrane being equally exposed to the perforin and granzymes, the lymphocytes invariably survive that encounter as they remain resistant to perforin pores. This project investigates the mechanisms behind this unique phenomenon.
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ItemImproving Ovarian Cancer Care Along The Disease Trajectory: From Prevention to Disease Management( 2019)The overarching objective of this thesis was to investigate key clinical care questions along the ovarian cancer disease trajectory and formulate strategies to improve care provision. This thesis focused on three time points on the trajectory: i) cancer prevention; ii) tolerability of experimental treatment at disease recurrence; and iii) development of malignant bowel obstruction. For women at high risk of developing ovarian cancer, such as those with a germline BRCA1 or BRCA2 mutation (gBRCA1/2mut), risk-reducing salpingo-oophorectomy (RRSO) is the most effective preventative method and recommended by peak bodies. RRSO involves complete resection of the ovaries and fallopian tubes up to the insertion into the cornua of the uterus. The resection of the fallopian tubes is necessary as it is known that BRCA1- and BRCA2-associated gynaecologic cancers appear to originate in the fimbrial end of the fallopian tubes rather than the ovaries, even though they have been typically labelled as “serous ovarian cancer”. Previous research had raised concerns that the quality of RRSO surgery and associated pathology evaluation performed in Australasian women had been suboptimal prior to 2008. I therefore undertook an investigation of the quality of contemporary RRSO and compared it with data from the historical research, examining the clinical predictors of RRSO quality. Across 78 institutions in Australia and New Zealand, a total of 164 study participants had RRSO performed and the quality of RRSO, in particularly the related pathology examination, had improved significantly compared to the previous report. The proportions of women who received adequate surgery and pathology evaluation were 99% and 66% respectively, compared to 91% and 23%, respectively (P<0.001) in the previous study. Implementable clinical strategies to potentially further improve quality were identified and included i) to direct RRSO referral to a gynaecologic oncologist (rather than general gynaecologist or general surgeon) and ii) to ensure the reporting pathologist is aware that the intent of surgery is risk-reduction in a high-risk woman, in order to prompt adequate processing and review of the RRSO specimens for occult cancer and pre-malignant lesions. In women with gBRCA1/2mut who undergo RRSO, whether hysterectomy should be performed at the time of RRSO to prevent uterine cancer was controversial. I therefore investigated the incidence of uterine cancer for Australasian gBRCA1/2mut carriers. Of the 828 eligible women identified from a prospective multi-institutional follow up study (kConFab), there were five cases of uterine cancer. Compared to the expected incidence in the Australian population, the standardised incidence ratio (SIR) was 2.45 (95%CI: 0.80-5.72; P=0.11). All five cases were of endometrioid adenocarcinoma histology and importantly, none had serous histology. Of those cases, three had a history of breast cancer and exposure to tamoxifen, a known risk factor for uterine cancer. Therefore, this finding did not justify the need for routine hysterectomy at the time of RRSO to reduce uterine cancer incidence in Australasian gBRCA1/2mut carriers. Disease progression in women with advanced ovarian cancer typically involves the omentum and peritoneum which causes abdominal symptoms. The goal of systemic treatment is to improve symptoms and delay further disease progression. Therefore, it is crucial that we consider the burden of treatment-related toxicities particularly in evaluation of novel drugs. Phase I clinical trials typically would include patients with different solid tumour types and are primarily intended to assess the safety and tolerability of investigational agents. Using the National Cancer Institute Phase I database, I performed a retrospective analysis of the adverse events (AEs) reported in women with gynaecological cancers compared to patients with other cancer types. Patients enrolled in the 150 phase I trials identified were divided into three groups to allow comparison; i) females with gynaecological cancers (n=685); ii) females with non-gynaecological cancers (n=1698); and iii) males with cancers (n=1886). Of those females with gynaecological cancers, the majority had ovarian cancer (n=527, 77%) followed by cervical cancer (n=76, 11%) and uterine cancer (n=72, 11%). Overall, females with gynaecological cancers were reported to have a significantly greater number of AEs during treatment (mean, 17.1 vs 14.7 vs 13.5, P<0.001), despite being similar at baseline (mean 7.0 vs 7.4 vs 7.0, P=0.09). In terms of AE severity, the main difference was a higher prevalence of grade 2 AEs reported in women with gynaecological cancers (mean 4.6 vs 3.9 vs 3.5). The five most prevalent AEs in women with gynaecological cancers were nausea (n=617, 90%), fatigue (n=587, 86%), anaemia (n=381, 56%), anorexia (n=357, 52%) and vomiting (n=355, 52%). These findings highlighted the need to improve the management for low-grade AEs in particular abdominal-related AEs for women with gynaecological cancers being treated on clinical trials. The inclusion of specific supportive care protocols/strategies into clinical trial protocols will better address symptom burden and improve quality of life. Malignant bowel obstruction (MBO) is a common complication for women with recurrent ovarian cancer that causes protracted and debilitating symptoms. Recognising variation in clinical practice and the unmet need for evidence-based treatment, I conducted a literature review to summarise current treatment strategies for MBO in women with advanced gynaecological cancers from a multidisciplinary perspective. A pilot interprofessional MBO program was developed by the MBO working group (which I co-led with Dr Stephanie Lheureux) and implemented in June 2016 at Princess Margaret Cancer Centre to support women who had, or were at risk, of developing MBO. The integrated model of care consisted of: i) standardised MBO symptom triage tools; ii) establishment of MBO multidisciplinary case conferences; iii) consensus on MBO care algorithms for in-patients and out-patients; iv) development of patient education materials for MBO; and v) prompt access to allied health professionals and supported advanced care planning. To assess the impact of the interprofessional MBO program, I reviewed all consecutive patients presenting with MBO from April 2014 to March 2018 (i.e. before and after the implementation of the program) and compared their outcomes. Of the 169 patients included, the majority (n=124, 73%) had recurrent ovarian cancer. There were 106 patients admitted prior to implementation of the MBO program (baseline group) whilst 63 patients were managed under the MBO program (MBO program group). Overall, the MBO program group had a significantly shorter average accumulated hospital length of stay (LOSsum) by 9 days (13 vs 22 days, adjusted P=0.006). Furthermore, their median overall survival post MBO diagnosis was approximately 5 months longer compared to the baseline group (243 vs 99 days, P=0.002). This retrospective, single institution study suggests a beneficial impact towards improving the complex care of women with advanced gynaecological cancers who developed MBO. Following on from this retrospective study, I developed a prospective MBO study incorporating patient reported outcomes to validate these findings, which is currently recruiting (MAMBO study, N=61/150 NCT03260647). In conclusion, the body of academic work carried out in this thesis has addressed known clinical gaps in ovarian cancer care throughout the disease trajectory and generated specific care recommendations to guide risk-reducing surgery management, to improve symptom burden whilst undergoing cancer treatment, and to improve management of malignant bowel obstruction. Broadly, this research will help clinicians, peak bodies and health funders implement evidence based care and institutional and national policies to facilitate better care provision for patients with ovarian cancer.
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ItemThe control of melanoma by the Hippo pathway( 2018)Melanoma is an aggressive cancer with extremely unfavourable prognosis. Two main types of melanoma include cutaneous melanoma (CM) accounting for around 95% and uveal melanoma (UM) around 5%. In Australia, melanoma is in the top five most commonly diagnosed cancers, estimated to contribute to over 10% of all new cancer diagnoses in 2017 (Cancer Australia, 2018.). While the overall death rate caused by all cancer is decreasing, the mortality of melanoma has increased in recent years (Howlader et al., 2012; AIHW, 2017). Patients diagnosed only with primary melanoma have relatively high survival rates, whereas when patients are diagnosed with metastatic melanoma, the survival rate is very low (Gershenwald et al., 2017). Currently, the mechanisms that drive melanoma progression and metastasis remain poorly understood; but better therapies are definitely required. BRAF mutations are most common in melanoma, occurring in around 50% of this disease (Akbani et al., 2015), which provides a possibility for targeted therapy. Indeed, the United States Food and Drug Administration (USFDA) has approved BRAF inhibitors (BRAFi) and MEK inhibitors (MEKi) as the standard treatment for metastatic melanoma patients harbouring BRAF mutations. However, drug resistance occurs in the majority of these patients within two years of treatment (Long et al., 2016). Therefore there is an urgent need to understand the mechanism of BRAFi and MEKi resistance, and find new therapeutic strategies for melanoma. One gene that has been linked to BRAFi resistance is the YAP, which is the key downstream effector of a pathway called the Hippo pathway. The Hippo pathway is an important regulator of organ growth in development. Deregulation of the Hippo pathway stimulates the activity of the YAP oncoprotein, which can cause several human cancers (Zanconato, Cordenonsi and Piccolo, 2016). However, the impacts of YAP deregulation in melanoma are not thoroughly understood. In this project, the roles of YAP in melanoma were examined. Firstly, the impacts of knockdown, overexpression, and activation of YAP on anchorage-independent growth of melanoma cells were assessed using soft agar assays. The results showed that either YAP activation or overexpression promotes colony formation, whilst YAP knockdown reduces this, suggesting potential influences of YAP on melanoma tumorigenesis. Secondly, the effects of YAP in melanoma invasion and metastasis were investigated. Melanoma cells stably expressing an active YAP mutant (YAP-5SA) have a greater invasive ability, as determined with transwell invasion assays. A spontaneous murine metastasis model was used to investigate the impact of YAP on metastasis. The results demonstrated that YAP-5SA promotes metastasis to multiple organs such as the lung and the liver; YAP-5SA enhances vascularity and necrosis of primary melanoma. Thirdly, mechanisms responsible for YAP-induced invasion were explored. Four potential target genes of YAP, derived from RNA-sequencing data, were found crucial, as well as the key YAP transcription factor partners, TEAD1-4. Finally, a lipid-lowering drug called simvastatin was found to kill melanoma cells and inhibits YAP activity in vitro. A post-translational modification, geranylgeranylation, was found to be essential in the statin-induced melanoma cell death and YAP inactivation; RhoA and other geranylgeranylated proteins might be important in these phenotypes. To conclude, this study explored the role of YAP in melanoma metastatic progression, and identified crucial transcription factors and target genes that mediate YAP-induced impacts on melanoma invasion. Additionally, inhibition of YAP and its mechanism in melanoma cells was preliminarily assessed using simvastatin. Understanding the molecular mechanism of melanoma metastasis and inhibition may help us establish more effective therapies for this disease.
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ItemInvestigating the requirements of pro-inflammatory signaling in skin and head and neck SCC( 2018)Head and neck squamous cell carcinoma (HNSCC) is a genetically heterogeneous cancer with poor prognosis. Current treatments for HNSCC are ineffective, and the resistance to therapies is often associated with a prominent inflammatory response highlighting the importance of devising ways to overcome it. Our laboratory has identified the Grainyhead-like 3 (GRHL3) gene as a potent tumor suppressor against HNSCC of both mice and humans. Loss of Grhl3 in mice induced HNSCC that appeared to be promoted by inflammation. In humans, we have introduced a paradigm shift in HNSCC pathogenesis through the identification of a miRNA-21-oncogenic network in patients, stratifying them into three subsets with distinct molecular signatures. This raised the hypotheses that inflammation may cooperate with the miR-21 oncogenic network to trigger human HNSCC and that different pro-inflammatory signaling might occur specifically in each HNSCC subset. In this study, we profiled pro-inflammatory cytokines/chemokines and their associated signaling pathways in 12 cell lines and xenografts by qPCR, Western Blot and immunohistochemistry, and correlated findings in cell lines with those in HNSCC mouse models as well as HNSCC patients. Our data determined that the expression of multiple cytokines and inflammatory proteins is dysregulated leading to the involvement of pivotal signaling such as the IL-1/NF-κB, the IL-6R/STAT3 and the TGF-β/SMAD pathways. We then modulated the pro-inflammatory signaling through different inhibitors, gene silencing and overexpression. The cell lines showed various sensitivities to the inhibitors of these inflammatory signaling, confirming the presence of distinct inflammatory profile in subsets of HNSCC. Interestingly, the antimicrobial peptides S100A8 and S100A9, which are involved in inflammation, were lost in all HNSCC cell lines in consistence with clinical data implicating them in the suppression of HNSCC. Thus, S100A8/A9 may function as tumor suppressors in HNSCC, and are currently being investigated to uncover the mechanisms that lead to their loss and to assess the downstream signaling of their epithelial RANGE and TRL4 receptors. Moreover, hotspot mutations were identified in common genes among the HNSCC cell lines, which showed different expression profiles of these mutant genes. Based on the pro-inflammatory signatures we have identified in human HNSCC lines, we are now able to stratify them into subsets with specific inflammatory pathways. Components of these pathways could serve as potential targets to overcome resistance in heterogeneous HNSCC. Inhibition of the miR-21 oncogenic network in combination with inhibitors of the inflammatory signaling while considering the mutational profiles may provide a better strategy to design new therapeutic applications in subtypes of HNSCC.