Orbital Apex Metastases From Primary Colorectal Adenocarcinoma: A Rare Cause for Unilateral Vision Loss.

Colorectal cancer is one of the most common causes of cancer-related death in the United States. Although it frequently metastasizes to adjacent structures such as the liver, orbital metastases are exceedingly uncommon. Additionally, the morbidity and mortality associated with colorectal cancer appear to be shifting to a younger population, a phenomenon that is exacerbated in minority populations. We present a case of orbital metastasis from colorectal carcinoma in a young Hispanic male. This uncommon presentation of disease emphasizes the link between healthcare disparity and differential outcomes of colorectal cancer.

Cancer incidence and outcomes registries in an Australian context: a systematic review.

BACKGROUND: Multiple cancer registries in Australia are used to track the incidence of cancer and the outcomes of their treatment. These registries can be broadly classed into a few types with an increasing number of registries comes a greater potential for collaboration and linkage. This article aims to critically review cancer registry types in Australia and evaluate the Australian Cancer registry landscape to identify these areas. METHODS: A systematic review was performed through MEDLINE, EMBASE and Cochrane Library, updated to September 2022 using a predefined search strategy. Inclusion criteria were those that only analysed Australian and/or New Zealand based cancer registries, appraised the utility of cancer outcomes and/or incidence registries, and explored the utility of linked databases using cancer outcomes and/or incidence registries. The grey literature was searched for all operating cancer registries in Australia. Details of registry infrastructure was extracted for analysis and comparison. RESULTS: Three thousand two hundred and sixteen articles identified from the three databases. Twelve met the inclusion criteria. Twenty-eight registries were identified using the grey literature. Strengths and weaknesses of Cancer Outcome Registries(COR) and Cancer Incidence Registries(CIR) were compared. Data linkage between registries or with other healthcare databases show great benefits in improving evidence for cancer research but are challenging to implement. Both registry types utilize differing modes of administration, influencing their accuracy and completeness. CONCLUSION: Outcome registries provide detailed data but their weakness lies in incomplete data coverage. Incidence registries record a large dataset which contain inaccuracies. Improving coverage of quality outcome registries, and quality assurance of data in incidence registries is required to ensure collection of accurate, meaningful data. Areas for collaboration identified included establishment of defined definitions and outcomes, data linkage between registry types or with healthcare databases, and collaboration in logistical planning to improve clinical utility of cancer registries.

Noncoding SNP at rs1663689 represses ADGRG6 via interchromosomal interaction and reduces lung cancer progression.

A previous genome-wide association study (GWAS) revealed an association of the noncoding SNP rs1663689 with susceptibility to lung cancer in the Chinese population. However, the underlying mechanism is unknown. In this study, using allele-specific 4C-seq in heterozygous lung cancer cells combined with epigenetic information from CRISPR/Cas9-edited cell lines, we show that the rs1663689 C/C variant represses the expression of ADGRG6, a gene located on a separate chromosome, through an interchromosomal interaction of the rs1663689 bearing region with the ADGRG6 promoter. This reduces downstream cAMP-PKA signaling and subsequently tumor growth both in vitro and in xenograft models. Using patient-derived organoids, we show that rs1663689 T/T-but not C/C-bearing lung tumors are sensitive to the PKA inhibitor H89, potentially informing therapeutic strategies. Our study identifies a genetic variant-mediated interchromosomal interaction underlying ADGRG6 regulation and suggests that targeting the cAMP-PKA signaling pathway may be beneficial in lung cancer patients bearing the homozygous risk genotype at rs1663689.

Position statement on the management of the immune checkpoint inhibitor-induced colitis via multidisciplinary modified Delphi consensus.

INTRODUCTION: The use of immune checkpoint inhibitors (ICIs) in cancer immunotherapy has shown increased overall survival in a wide range of cancer types with the associated risk of developing severe immune-mediated adverse events, commonly involving the gastrointestinal tract. AIM: The aim of this position statement is to provide an updated practice advice to the gastroenterologists and oncologists on the diagnosis and management of ICI-induced gastrointestinal toxicity. METHODOLOGY: The evidence reviewed in this paper includes a comprehensive search strategy of English language publications. Consensus was reached using a three-round modified Delphi methodology and approved by the members of the Belgian Inflammatory Bowel Disease Research and Development Group (BIRD), Belgian Society of Medical Oncology (BSMO), Belgian group of Digestive Oncology (BGDO), and Belgian Respiratory Society (BeRS). CONCLUSIONS: The management of ICI-induced colitis requires an early multidisciplinary approach. A broad initial assessment is necessary (clinical presentation, laboratory markers, endoscopic and histologic examination) to confirm the diagnosis. Criteria for hospitalisation, management of ICIs, and initial endoscopic assessment are proposed. Even if corticosteroids are still considered the first-line therapy, biologics are recommended as an escalation therapy and as early treatment in patients with high-risk endoscopic findings.

Effects of immunosuppressive treatment on patient outcomes after immune checkpoint inhibitor-related gastrointestinal toxicity.

PURPOSE: Immune checkpoint inhibitors (ICIs) are increasingly used in the treatment of certain cancers but cause immune-related adverse events (irAEs). Gastrointestinal irAEs may necessitate extended periods of steroid use and the initiation of selective immunosuppressive therapy (SIT) which could theoretically counteract the effect of ICIs. In this study, we aim to explore the impact of immunosuppression use and duration on cancer progression and progression-free survival (PFS). METHODS: This is a single-center retrospective review exploring cancer outcomes in patients taking ICIs who developed gastrointestinal irAEs within 1 year of ICI initiation. Cancer outcome and progression free survival (PFS) were measured and compared by using IBM SPSS Statistics 26. RESULTS: Of the 116 patients included in this study, 69 received immunosuppression to treat irAEs. The occurrence of colitis and use of immunosuppression for colitis were associated with less cancer progression by later assessment (p < 0.05). Shorter durations of steroids with or without SIT for colitis were associated with less cancer progression within the study window than no immunosuppression (p < 0.05). Immunosuppression has no effect on PFS (p < 0.05). CONCLUSION: Our study reported shorter duration of steroid treatment for colitis may be associated with less cancer progression. Though the use of immunosuppression was not found to impact PFS, this may be confounded by the presence of colitis, which is known to improve cancer outcomes and could mask any negative impact of immunosuppression on survival. It may be preferable to limit long-term immunosuppression in the treatment of immune-mediated colitis to minimize potential complications. Prospective studies are needed to clarify this relationship, and treatments that abrogate the need for immunosuppression in these patients such as fecal microbiota transplantation.

Prospective study and proposal of an outcome predictive nomogram in a consecutive prospective series of differentiated thyroid cancer based on the new ATA risk categories and TNM.

Introduction: The personalized management of differentiated thyroid cancer (DTC) is currently based on the postoperative TNM staging system and the ATA risk stratification system (RSS), both updated in 2018 and 2015, respectively. Purpose: We aimed to evaluate the impact of the last two editions of TNM and ATA RSS in the prediction of persistent/recurrent disease in a large series of DTC patients. Patients and methods: Our prospective study included 451 patients undergone thyroidectomy for DTC. We classified the patients according to TNM (both VIII and VII ed.) and stratified them according to the ATA RSS (both 2015 and 2009). We then evaluated the response to the initial therapy after 12-18 months according to the ATA "ongoing" risk stratification, and analyzed the variables associated with persistent/recurrent disease by multivariate analysis. Results: The performance of the last two ATA RSSs was not significantly different. By staging patients according to the VIII or VII TNM editions, we found significant differences only in the distribution of patients with structural disease classified in stages III and IV. At multivariate analysis, only T-status and N-status were independently associated with persistent/recurrent disease. Overall, ATA RSSs and TNMs showed low predictive power in terms of persistent/recurrent disease (by Harrell's test). Conclusions: In our series of DTC patients, the new ATA RSS as well as the VIII TNM staging provided no additional benefit compared to the previous editions. Moreover, the VIII TNM staging system may underestimate disease severity in patients with large and numerous lymph node metastases at diagnosis.

Diagnosis, treatment and survival from bladder, upper urinary tract, and urethral cancers: real-world findings from NHS England between 2013 and 2019.

OBJECTIVE: We report NHS England data for patients with bladder cancer (BC), upper tract urothelial cancer (UTUC: renal pelvic and ureteric), and urethral cancers from 2013 to 2019. MATERIALS AND METHODS: Hospital episode statistics, waiting times, and cancer registrations were extracted from NHS Digital. RESULTS: Registrations included 128 823 individuals with BC, 16 018 with UTUC, and 2533 with urethral cancer. In 2019, 150 816 persons were living with a diagnosis of BC, of whom 113 067 (75.0%) were men, 85 117 (56.5%) were aged >75 years, and 95 553 (91.7%) were Caucasian. Incidence rates were stable (32.7-34.3 for BC, 3.9-4.2 for UTUC and 0.6-0.7 for urethral cancer per 100 000 population). Most patients 52 097 (mean [range] 41.3% [40.7-42.0%]) were referred outside the 2-week-wait pathway and 15 340 (mean [range] 12.2% [11.7-12.6%]) presented as emergencies. Surgery, radiotherapy, chemotherapy, or multimodal treatment use varied with disease stage, patient factors and Cancer Alliance. Between 27% and 29% (n = 6616) of muscle-invasive BCs did not receive radical treatment. Survival rates reflected stage, grade, location, and tumour histology. Overall survival rates did not improve over time (relative change: 0.97, 95% confidence interval 0.97-0.97) at 2 years in contrast to other cancers. CONCLUSION: The diagnostic pathway for BC needs improvement. Increases in survival might be delivered through greater use of radical treatment. NHS Digital data offers a population-wide picture of this disease but does not allow individual outcomes to be matched with disease or patient features and key parameters can be missing or incomplete.

Outcomes of SARS-CoV-2 infection in cancer versus non-cancer-patients: a population-based study in northeastern Italy.

INTRODUCTION: This study assesses the risk of infection and clinical outcomes in a large consecutive population of cancer and non-cancer patients tested for SARS-CoV-2 status. METHODS: Study patients underwent SARS-CoV-2 molecular-testing between 22 February 2020 and 31 July 2020, and were found infected (CoV2+ve) or uninfected. History of malignancy was obtained from regional population-based cancer registries. Cancer-patients were distinguished by time between cancer diagnosis and SARS-CoV-2 testing (<12/⩾12 months). Comorbidities, hospitalization, and death at 15 September 2020 were retrieved from regional population-based databases. The impact of cancer history on SARS-CoV-2 infection and clinical outcomes was calculated by fitting a multivariable logistic regression model, adjusting for sex, age, and comorbidities. RESULTS: Among 552,362 individuals tested for SARS-CoV-2, 55,206 (10.0%) were cancer-patients and 22,564 (4.1%) tested CoV2+ve. Irrespective of time since cancer diagnosis, SARS-CoV-2 infection was significantly lower among cancer patients (1,787; 3.2%) than non-cancer individuals (20,777; 4.2% - Odds Ratio (OR)=0.60; 0.57-0.63). CoV2+ve cancer-patients were older than non-cancer individuals (median age: 77 versus 57 years; p<0.0001), were more frequently men and with comorbidities. Hospitalizations (39.9% versus 22.5%; OR=1.61; 1.44-1.80) and deaths (24.3% versus 9.7%; OR=1.51; 1.32-1.72) were more frequent in cancer-patients. CoV2+ve cancer-patients were at higher risk of death (lung OR=2.90; 1.58-5.24, blood OR=2.73; 1.88-3.93, breast OR=1.77; 1.32-2.35). CONCLUSIONS: The risks of hospitalization and death are significantly higher in CoV2+ve individuals with past or present cancer (particularly malignancies of the lung, hematologic or breast) than in those with no history of cancer.

omicsGAT: Graph Attention Network for Cancer Subtype Analyses.

The use of high-throughput omics technologies is becoming increasingly popular in all facets of biomedical science. The mRNA sequencing (RNA-seq) method reports quantitative measures of more than tens of thousands of biological features. It provides a more comprehensive molecular perspective of studied cancer mechanisms compared to traditional approaches. Graph-based learning models have been proposed to learn important hidden representations from gene expression data and network structure to improve cancer outcome prediction, patient stratification, and cell clustering. However, these graph-based methods cannot rank the importance of the different neighbors for a particular sample in the downstream cancer subtype analyses. In this study, we introduce omicsGAT, a graph attention network (GAT) model to integrate graph-based learning with an attention mechanism for RNA-seq data analysis. The multi-head attention mechanism in omicsGAT can more effectively secure information of a particular sample by assigning different attention coefficients to its neighbors. Comprehensive experiments on The Cancer Genome Atlas (TCGA) breast cancer and bladder cancer bulk RNA-seq data and two single-cell RNA-seq datasets validate that (1) the proposed model can effectively integrate neighborhood information of a sample and learn an embedding vector to improve disease phenotype prediction, cancer patient stratification, and cell clustering of the sample and (2) the attention matrix generated from the multi-head attention coefficients provides more useful information compared to the sample correlation-based adjacency matrix. From the results, we can conclude that some neighbors play a more important role than others in cancer subtype analyses of a particular sample based on the attention coefficient.

Is multifocality a risk factor in low-risk papillary thyroid cancer?

INTRODUCTION: Multifocality in papillary thyroid cancer (PTC) is a common event, ranging from 18% to 87%. Additional multiple foci are frequently very small and generally detected in pathology specimens. The mechanisms of intrathyroidal spread, and its correlation with age, gender, tumour size, and lymph node metastases remain unclear. Moreover, studies assessing the prognostic impact of PTC multifocality have yielded non-univocal results. We aimed to evaluate the following: a) the histopathological and clinical characteristics associated with multifocal PTC; and b) the impact of multifocality on the long-term outcome. MATERIAL AND METHODS: We analysed a consecutive series of 2814 PTC patients without evidence of microscopic extrathyroidal extension (T1a, T1b, and T2), all of whom had undergone total thyroidectomy and were followed-up (median 4.7 years) in our thyroid clinic. Females comprised 81.3% and males 18.7% (F/M = 4.4/1), with a median age at diagnosis of 45.0 years. Patients were subdivided into 2 groups: 72.7% unifocal tumour and 27.3% multifocal tumour. Post-surgical radioiodine ablation (RAI) (30-100 mCi of 131-I) was performed in 1425 (50.6%) patients. All patients were periodically followed with thyroglobulin and anti-thyroglobulin antibodies measurements and with neck ultrasonography under L-thyroxine therapy and subjected to additional radioiodine administration or another therapeutic measure if not cured. RESULTS: Patients in the multifocal group were older (median age 46.4 vs. 44.5 years, respectively, p < 0.05) and presented a lower F/M ratio (F/M = 3.7/1 and 4.7/1; p = 0.01). T1a and T1b tumours showed no significant difference in multifocality rate whereas T2 tumours were less frequently multifocal (14.2% vs. 10.9%, p < 0.05). Multifocal tumours were more frequent in N1b (11.3% vs. 7.8%, p < 0.01) and less frequent in Nx (50.5% vs. 56.8%, p < 0.01), with no difference between the N0 and N1a groups. The clinical outcome was similar in the 2 group of patients (88.2 % in the unifocal group vs. 90.2% in the multifocal group). CONCLUSIONS: Multifocality is more frequent in older and male patients, in smaller tumours, and in N1b. However, multifocality "per se" was not associated, in our study, with worse clinical outcome in PTC patients.

Incidence and Outcomes of Early Cancers After Kidney Transplantation.

Outcomes of early cancers after kidney transplantation are not well-understood. We included recipients of first live and deceased donor kidney transplants who developed de novo cancers in Australia and New Zealand between 1980-2016. We compared the frequency and stage of specific cancer types that developed early (≤12-months) and late (>12-months) post-transplantation. Risk factors for death were evaluated using multivariable Cox regression analyses. Of 2,759 recipients who developed de novo cancer, followed-up for 40,035 person-years, 243 (8.8%) patients were diagnosed with early cancer. Post-transplant lymphoproliferative disease, urinary cancers and melanoma were the most common cancer types (26%, 18%, and 12%) and the majority were either in-situ or locally invasive lesions (55%, 84%, and 86%). Tumors arising early from the gastrointestinal and respiratory systems were uncommon but aggressive, with 40% presenting with metastatic disease at time of diagnosis. Overall, 32% of patients with early cancers died within a median of 4.7 months (IQR:0.6-16) post-diagnosis and 91% were cancer-related deaths. Older recipient and donor age were associated with an increased risk of all-cause death. Early cancers, though infrequent in kidney transplant recipients, are associated with poor outcomes, as nearly 1 in 3 died from cancer-related death; with majority of deaths occurring within 12-months of cancer diagnosis.

Training radiomics-based CNNs for clinical outcome prediction: Challenges, strategies and findings.

Radiological images play a central role in radiotherapy, especially in target volume delineation. Radiomic feature extraction has demonstrated its potential for predicting patient outcome and cancer risk assessment prior to treatment. However, inherent methodological challenges such as severe class imbalance, small training sample size, multi-centre data and weak correlation of image representations to outcomes are yet to be addressed adequately. Current radiomic analysis relies on segmented images (e.g., of tumours) for feature extraction, leading to loss of important context information in surrounding tissue. In this work, we examine the correlation between radiomics and clinical outcomes by combining two data modalities: pre-treatment computerized tomography (CT) imaging data and contours of segmented gross tumour volumes (GTVs). We focus on a clinical head & neck cancer dataset and design an efficient convolutional neural network (CNN) architecture together with appropriate machine learning strategies to cope with the challenges. During the training process on two cohorts, our algorithm learns to produce clinical outcome predictions by automatically extracting radiomic features. Test results on two other cohorts show state-of-the-art performance in predicting different clinical endpoints (i.e., distant metastasis: AUC = 0.91; loco-regional failure: AUC = 0.78; overall survival: AUC = 0.70 on segmented CT data) compared to prior studies. Furthermore, we also conduct extensive experiments both on the whole CT dataset and a combination of CT and GTV contours to investigate different learning strategies for this task. For example, further experiments indicate that overall survival prediction significantly improves to 0.83 AUC by combining CT and GTV contours as inputs, and the combination provides more intuitive visual explanations for patient outcome predictions.

Mask-Guided Convolutional Neural Network for Breast Tumor Prognostic Outcome Prediction on 3D DCE-MR Images.

In this proof-of-concept work, we have developed a 3D-CNN architecture that is guided by the tumor mask for classifying several patient-outcomes in breast cancer from the respective 3D dynamic contrast-enhanced MRI (DCE-MRI) images. The tumor masks on DCE-MRI images were generated using pre- and post-contrast images and validated by experienced radiologists. We show that our proposed mask-guided classification has a higher accuracy than that from either the full image without tumor masks (including background) or the masked voxels only. We have used two patient outcomes for this study: (1) recurrence of cancer after 5 years of imaging and (2) HER2 status, for comparing accuracies of different models. By looking at the activation maps, we conclude that an image-based prediction model using 3D-CNN could be improved by even a conservatively generated mask, rather than overly trusting an unguided, blind 3D-CNN. A blind CNN may classify accurately enough, while its attention may really be focused on a remote region within 3D images. On the other hand, only using a conservatively segmented region may not be as good for classification as using full images but forcing the model's attention toward the known regions of interest.

Assessing the impact of COVID-19 on liver cancer management (CERO-19).

BACKGROUND & AIMS: The coronavirus disease 2019 (COVID-19) pandemic has posed unprecedented challenges to healthcare systems and it may have heavily impacted patients with liver cancer (LC). Herein, we evaluated whether the schedule of LC screening or procedures has been interrupted or delayed because of the COVID-19 pandemic. METHODS: An international survey evaluated the impact of the COVID-19 pandemic on clinical practice and clinical trials from March 2020 to June 2020, as the first phase of a multicentre, international, and observational project. The focus was on patients with hepatocellular carcinoma or intrahepatic cholangiocarcinoma, cared for around the world during the first COVID-19 pandemic wave. RESULTS: Ninety-one centres expressed interest to participate and 76 were included in the analysis, from Europe, South America, North America, Asia, and Africa (73.7%, 17.1%, 5.3%, 2.6%, and 1.3% per continent, respectively). Eighty-seven percent of the centres modified their clinical practice: 40.8% the diagnostic procedures, 80.9% the screening programme, 50% cancelled curative and/or palliative treatments for LC, and 41.7% modified the liver transplantation programme. Forty-five out of 69 (65.2%) centres in which clinical trials were running modified their treatments in that setting, but 58.1% were able to recruit new patients. The phone call service was modified in 51.4% of centres which had this service before the COVID-19 pandemic (n = 19/37). CONCLUSIONS: The first wave of the COVID-19 pandemic had a tremendous impact on the routine care of patients with liver cancer. Modifications in screening, diagnostic, and treatment algorithms may have significantly impaired the outcome of patients. Ongoing data collection and future analyses will report the benefits and disadvantages of the strategies implemented, aiding future decision-making. LAY SUMMARY: The coronavirus disease 2019 (COVID-19) pandemic has posed unprecedented challenges to healthcare systems globally. Herein, we assessed the impact of the first wave pandemic on patients with liver cancer and found that routine care for these patients has been majorly disrupted, which could have a significant impact on outcomes.

Vitamin C Intake and Cancers: An Umbrella Review.

Based on the existing systematic reviews and meta-analyses, we conducted this umbrella review aiming at evaluating the quality of evidence, validity and biases of the relationship between vitamin C (VC) intake and incidence and outcomes of multiple cancers. We identified 22 cancer outcomes within 3,562 articles. VC consumption was associated with lower incidence of bladder cancer, breast cancer, cervical tumors, endometrial cancer, esophageal cancer, gastric cancer, glioma, lung cancer, pancreatic cancer, prostate cancer, renal cell cancer, and total cancer occurrence. VC intake was also related to decreased risk of breast cancer prognosis (recurrence, cancer-specific mortality, and all-cause mortality).

Genomic and epigenetic aberrations of chromosome 1p36.13 have prognostic implications in malignancies.

Deletions of chromosome 1p36 are common in malignancies; however, there is limited information regarding the biological and prognostic implications of 1p36 in cancer. Steroid Receptor-Associated and Regulated Protein (SRARP) is a tumor suppressor on chromosome 1p36.13 that its inactivation predicts poor cancer outcome, indicating that the 1p36.13 segment requires further studies. Therefore, a comprehensive multi-omics analysis of The Cancer Genome Atlas (TCGA), the Pan-Cancer Analysis of Whole Genomes (PCAWD), the International Cancer Genome Consortium (ICGC), and the Genomic Data Commons (GDC) Pan-Cancer datasets was conducted to investigate the prognostic implications of 1p36.13 in malignancies. This study revealed that expression and DNA methylation of multiple genes on 1p36.13 are significantly associated with survival in primary tumors and normal adjacent tissues. In addition, copy-number loss in every gene on 1p36.13 predicts poor cancer outcome. Importantly, copy-number loss and somatic mutations of chromosome 1p36.13 segment are associated with worse survival in primary tumors, and DNA hypermethylation of 1p36.13 predicts poor outcome in normal adjacent tissues. Therefore, genomic and epigenetic aberrations of chromosome 1p36.13 have promising prognostic implications in cancer.

The Contribution of Race to Breast Tumor Microenvironment Composition and Disease Progression.

Breast cancer is the second most commonly diagnosed cancer in American women following skin cancer. Despite overall decrease in breast cancer mortality due to advances in treatment and earlier screening, black patients continue to have 40% higher risk of breast cancer related death compared to white patients. This disparity in outcome persists even when controlled for access to care and stage at presentation and has been attributed to differences in tumor subtypes or gene expression profiles. There is emerging evidence that the tumor microenvironment (TME) may contribute to the racial disparities in outcome as well. Here, we provide a comprehensive review of current literature available regarding race-dependent differences in the TME. Notably, black patients tend to have a higher density of pro-tumorigenic immune cells (e.g., M2 macrophages, regulatory T cells) and microvasculature. Although immune cells are classically thought to be anti-tumorigenic, increase in M2 macrophages and angiogenesis may lead to a paradoxical increase in metastasis by forming doorways of tumor cell intravasation called tumor microenvironment of metastasis (TMEM). Furthermore, black patients also have higher serum levels of inflammatory cytokines, which provide a positive feedback loop in creating a pro-metastatic TME. Lastly, we propose that the higher density of immune cells and angiogenesis observed in the TME of black patients may be a result of evolutionary selection for a more robust immune response in patients of African geographic ancestry. Better understanding of race-dependent differences in the TME will aid in overcoming the racial disparity in breast cancer mortality.

Steroid receptor-associated and regulated protein is a biomarker in predicting the clinical outcome and treatment response in malignancies.

BACKGROUND: Steroid receptor-associated and regulated protein (SRARP) has recently been identified as a novel tumor suppressor in malignancies of multiple tissue origins. SRARP is located on chromosome 1p36.13 and is widely inactivated by deletions and epigenetic silencing in malignancies. Therefore, additional studies are required to explore SRARP as a potential cancer biomarker. AIM: This study explores the application of SRARP as a novel biomarker in malignancies of multiple tissue origins using the analysis of large genomic datasets. METHODS AND RESULTS: A comprehensive genomic analysis of large cancer datasets was carried out to examine the association of SRARP expression and copy-number with molecular and clinical features in malignancies of multiple tissue origins. This study demonstrated that SRARP under-expression and copy-number loss are strongly associated with the loss of other tumor suppressors such as TP53 and NF1 mutations and oncogenic gains, including N-MYC amplification and ERG rearrangement, suggesting that SRARP inactivation is associated with wider genomic instability in malignancies. Importantly, SRARP under-expression and copy-number loss are strong predictors of poor clinical and/or pathological features in breast, colorectal, lung, prostate, gastric, endometrial, cervical, brain, ovarian, bladder, thyroid, and hepatocellular cancers as well as neuroblastoma, uveal melanoma, and acute myeloid leukemia with highly significant odds ratios. Finally, higher SRARP expression and copy-number predict a better response to several cancer drugs. CONCLUSION: This study suggests that the SRARP inactivation presents a robust biomarker in predicting molecular and clinicopathological features, and treatment response in malignancies.