CONTEXT: - The world of oncology has changed dramatically in the past few years with the introduction of checkpoint inhibitors and immunotherapy. The promising findings of a small, phase 2 clinical trial that led to the US Food and Drug Administration breakthrough designation and approval of the anti-programmed death receptor-1 (PD-1) drug pembrolizumab (Keytruda, Merck, Kenilworth, New Jersey) to treat metastatic/refractory microsatellite instability-high colorectal cancer (CRC) has significantly boosted interest in immunomodulatory therapies in microsatellite instability-high CRC.
OBJECTIVES: - To review the immune response to cancer and the role of immune checkpoints, focusing on the technical and interpretation challenges of PD-1/programmed death ligand-1 (PD-L1) testing by pathologists and the clinical implications of the test and the therapeutic potential of treating CRC with checkpoint inhibitors.
DATA SOURCES: - A PubMed review was performed of articles pertaining to CRC, microsatellite instability and mismatch repair systems, molecular classification, immune response, PD-1/PD-L1, and immunotherapy.
CONCLUSIONS: - Exciting success with anti-PD-1/PD-L1 and anticytotoxic T-lymphocyte-associated protein 4 (CTLA4) checkpoint inhibitors has already been reported in melanoma and in lung and renal carcinomas. Recently, microsatellite instability-high CRCs, expressing PD-L1 by immunohistochemistry, regardless of the level of that PD-L1 expression, appeared to respond to checkpoint blockades with anti-PD-1 or anti-PD-L1 agents, whereas microsatellite-stable tumors were much less responsive. With microsatellite instability routinely tested by most centers, studies that include larger cohorts are required to study the predictive role of PD-1/PD-L1 expression in microsatellite instability-high CRC, to assess which immunohistochemistry antibodies to use, to refine the scoring criteria, and to critically analyze the interpretation pitfalls.
Immune checkpoint blockade has revolutionized cancer treatment. In this issue of Cell, insights from a longitudinal multi-omics analysis of the largest yet-reported cohort of melanoma patients reveal how tumor and immunity co-evolve during anti-PD-1 therapy.
Abstract: Despite impressive clinical success, cancerimmunotherapy based on immune checkpoint blockade remains ineffective in many patients due to tumoral resistance... TiRP tumors resist immunotherapy based on checkpoint blockade, cancervaccines or adoptive T-cell therapy. TiRP tumors recruit and activate tumor-specific CD8(+) T cells, but these cells then undergo apoptosis.
Oncology (4), Vaccines (1) Neoplasms (14), Melanoma (2), more mentions
... moderate-grade disease, and 17% for high-grade disease; the corresponding risks of any recurrence or a contralateral breast cancer were 17%, 22%, and 26%, respectively AbstractText: After 5 years of adjuvant endocrine therapy, breast-cancer recurrences continued to occur steadily throughout the study period from 5 to 20 years.
Purpose Fear of cancer recurrence (FCR) is prevalent, distressing, and long lasting. This study evaluated the impact of a theoretically/empirically based intervention (ConquerFear) on FCR. Methods Eligible survivors had curable breast or colorectal cancer or melanoma, had completed treatment (not including endocrine therapy) 2 months to 5 years previously, were age > 18 years, and had scores above the clinical cutoff on the FCR Inventory (FCRI) severity subscale at screening. Participants were randomly assigned at a one-to-one ratio to either five face-to-face sessions of ConquerFear (attention training, metacognitions, acceptance/mindfulness, screening behavior, and values-based goal setting) or an attention control (Taking-it-Easy relaxation therapy). Participants completed questionnaires at baseline (T0), immediately post-therapy (T1), and 3 (T2) and 6 months (T3) later. The primary outcome was FCRI total score. Results Of 704 potentially eligible survivors from 17 sites and two online databases, 533 were contactable, of whom 222 (42%) consented; 121 were randomly assigned to intervention and 101 to control. Study arms were equivalent at baseline on all measured characteristics. ConquerFear participants had clinically and statistically greater improvements than control participants from T0 to T1 on FCRI total ( P < .001) and severity subscale scores ( P = .001), which were maintained at T2 ( P = .017 and P = .023, respectively) and, for FCRI total only, at T3 ( P = .018), and from T0 to T1 on three FCRI subscales (coping, psychological distress, and triggers) as well as in general anxiety, cancer-specific distress (total), and mental quality of life and metacognitions (total). Differences in FCRI psychological distress and cancer-specific distress (total) remained significantly different at T3. Conclusion This randomized trial demonstrated efficacy of ConquerFear compared with attention control (Taking-it-Easy) in reduction of FCRI total scores immediately post-therapy and 3 and 6 months later and in many secondary outcomes immediately post-therapy. Cancer-specific distress (total) remained more improved at 3- and 6-month follow-up.
AbstractText: Next-generation sequencing (NGS) of cancer gene panels are widely applied to enable personalized cancertherapy and to identify novel oncogenic mutations AbstractText: We performed targeted NGS on 932 clinical cases of non-small-cell lung cancers (NSCLCs) using the Ion AmpliSeq™ Cancer Hotspot panel v2 assay AbstractText: Actionable ...
... binding was scarcely detectable in other cell types including normal integrin β7(+) lymphocytes. T cells transduced with MMG49-derived chimeric antigen receptor (CAR) exerted anti-MM effects without damaging normal hematopoietic cells. Thus, MMG49 CAR T cell therapy is promising for MM, and a receptor protein with a rare but physiologically relevant conformation can serve as a cancerimmunotherapy target.
... standard clinical and trial practices, combined with improvements in our understanding of cancerbiology have resulted in the identification of a number of limitations of the ... situations reflect the consequences of prolonged control of metastatic disease using targeted therapies, thoracic oncology has generated many of the key scenarios requiring elucidation and/or improvements ...
Multivariable analysis did not demonstrate significant differences in TTP or OS AbstractText: In this study, the HSD3B1 (1245C) allele was associated with more rapid development of metastases in men treated with ADT for biochemical recurrence after primary radiation therapy for prostate cancer. Notably, 105 of 213 men (49%) had received prior ADT, and 119 of 213 (56%) received an androgen ...
Oncology (7) Prostatic Neoplasms (3), Neoplasms (1), more mentions
CONTEXT: Bacillus Calmette-Guérin (BCG) is currently the most effective intravesical therapy for nonmuscle invasive bladder cancer, reducing not only recurrence rates but also preventing progression and reducing deaths. However, response rates to BCG vary widely and are dependent on a multitude of factors.
OBJECTIVE: To review existing data on clinical, pathologic, immune, and molecular markers that allow prediction of BCG response.
EVIDENCE ACQUISITION: PubMed and MEDLINE search of English language literature was conducted from its inception to July 2017 using appropriate search terms. Following systematic literature review and analysis of data, consensus voting was used to generate the content of this review.
EVIDENCE SYNTHESIS: As seen in the EORTC and CUETO risk nomograms, clinicopathologic features, especially tumor stage and grade, are the most effective predictors of BCG response. Data are less robust with regards to the association of response with age, female sex, recurrent tumors, multiplicity of tumors, and the presence of carcinoma in situ. Single biomarkers, such as tumor p53 and urinary interleukin-2 expression, have had limited success in predicting BCG response, possibly due to the multifaceted nature of the generated immune response. More comprehensive biomarker panels (eg, urinary cytokines), have a more robust correlation with response, as do patterns of urinary cytologic fluorescent in-situ hybridization examination. Gene expression data correlate with disease progression, but studies examining potential associations with BCG response are limited.
CONCLUSIONS: Currently, the best predictors of BCG response are clinicopathologic features such as tumor grade and stage. Panels of urinary cytokines, as well as fluorescent in-situ hybridization patterns of cytologic anomalies, appear to be promising biomarkers. The complexity of the immune response to BCG and the heterogeneity of bladder cancer suggest that future studies should amalgamate measures reflecting innate immune response and tumor/stromal gene expression before these can be adopted for clinical use.
PATIENT SUMMARY: Bacillus Calmette-Guérin (BCG) immunotherapy is an effective treatment for many patients with nonmuscle invasive bladder cancer. An individual's response to BCG can be predicted by using various features of the cancer. In the future, predictive markers using molecular measures of the tumor type and the immune response to BCG may allow us to precisely know an individual's likely outcome after BCG treatment.
Oncology (5) Neoplasms (8), Urinary Bladder Neoplasms (4), Carcinoma in Situ (1), more mentions
Therapies targeting epidermal growth factor receptor (EGFR) have variable and unpredictable responses in breast cancer. Screening triple-negative breast cancer (TNBC) patient-derived xenografts (PDXs), we identify a subset responsive to EGFR inhibition by gefitinib, which displays heterogeneous expression of wild-type EGFR. Deep single-cell RNA sequencing of 3,500 cells from an exceptional responder identified subpopulations displaying distinct biological features, where elevated EGFR expression was significantly enriched in a mesenchymal/stem-like cellular cluster. Sorted EGFR(hi) subpopulations exhibited enhanced stem-like features, including ALDH activity, sphere-forming efficiency, and tumorigenic and metastatic potential. EGFR(hi) cells gave rise to EGFR(hi) and EGFR(lo) cells in primary and metastatic tumors, demonstrating an EGFR-dependent expansion and hierarchical state transition. Similar tumorigenic EGFR(hi) subpopulations were identified in independent PDXs, where heterogeneous EGFR expression correlated with gefitinib sensitivity. This provides new understanding for an EGFR-dependent hierarchy in TNBC and for patient stratification for therapeutic intervention.
... a direct effect on tumor-intrinsic factors, interplay with whole-body exercise effects, alleviation of cancer-related adverse events, and improvement of anti-cancer treatment efficacy. These findings have wide-ranging societal implications, as this understanding may lead to changes in cancer treatment strategies Keyword: biomarkers. Keyword: cancer. Keyword: cancertherapy. Keyword: cancer-related depression. Keyword: epinephrine. Keyword: exercise training.
Abstract: Immunotherapies, particularly checkpoint inhibitors, have set off a revolution in cancertherapy by releasing the power of the immune system. However, only little is known about the antigens that are essentially presented on cancer cells, capable of exposing them to immune cells. Large-scale HLA ligandome analysis has enabled us to exhaustively characterize the immunopeptidomic landscape of epithelial ovarian ...
... associated with PD-L1 positivity, and expression of immune related genes representing about 60% of MPM, represents a candidate subtype that may respond to cancerimmunotherapy AbstractText: These data suggest that 60% of MPM patients characterized by either PD-L1 expression or an inflamed status present an attractive candidate for ...
... CD95 and CD95L mRNA sequences and an unrelated control gene, Venus, we have identified many toxic sequences - most of them located in the open reading frame of CD95L. We propose that specific toxic RNAi-active sequences present in the genome can kill cancer cells Keyword: DISE. Keyword: Fas. Keyword: RNAi. Keyword: cancer. Keyword: cancerbiology. Keyword: cell biology. Keyword: human.
Cancer is a dynamic disease. During the course of disease, cancers generally become more heterogeneous. As a result of this heterogeneity, the bulk tumour might include a diverse collection of cells harbouring distinct molecular signatures with differential levels of sensitivity to treatment. This heterogeneity might result in a non-uniform distribution of genetically distinct tumour-cell subpopulations across and within disease sites (spatial heterogeneity) or temporal variations in the molecular makeup of cancer cells (temporal heterogeneity). Heterogeneity provides the fuel for resistance; therefore, an accurate assessment of tumour heterogeneity is essential for the development of effective therapies. Multiregion sequencing, single-cell sequencing, analysis of autopsy samples, and longitudinal analysis of liquid biopsy samples are all emerging technologies with considerable potential to dissect the complex clonal architecture of cancers. In this Review, we discuss the driving forces behind intratumoural heterogeneity and the current approaches used to combat this heterogeneity and its consequences. We also explore how clinical assessments of tumour heterogeneity might facilitate the development of more-effective personalized therapies.
Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for the successful development of standardized and automated analysis of patient data. One important goal of precision cancer medicine is the accurate prediction of optimal drug therapies from the genomic profiles of individual patient tumors. We introduce here an open source software platform that employs a highly versatile support vector machine (SVM) algorithm combined with a standard recursive feature elimination (RFE) approach to predict personalized drug responses from gene expression profiles. Drug specific models were built using gene expression and drug response data from the National Cancer Institute panel of 60 human cancer cell lines (NCI-60). The models are highly accurate in predicting the drug responsiveness of a variety of cancer cell lines including those comprising the recent NCI-DREAM Challenge. We demonstrate that predictive accuracy is optimized when the learning dataset utilizes all probe-set expression values from a diversity of cancer cell types without pre-filtering for genes generally considered to be "drivers" of cancer onset/progression. Application of our models to publically available ovarian cancer (OC) patient gene expression datasets generated predictions consistent with observed responses previously reported in the literature. By making our algorithm "open source", we hope to facilitate its testing in a variety of cancer types and contexts leading to community-driven improvements and refinements in subsequent applications.