Identification of molecular markers for the early detection of human squamous cell carcinoma of the uterine cervix

To identify novel cellular genes that could potentially act as predictive molecular markers for human cervical cancer, we employed RT–PCR differential display, reverse Northern and Northern blot analysis to compare the gene expression profiles between squamous cell carcinoma biopsies and adjacent histo-pathological normal epithelium tissues. Twenty-eight cDNA clones were isolated that were demonstrated to be consistently over-expressed in squamous cell cervical cancer biopsies of FIGO stages 1B to 3B. Most importantly, it was observed that, in addition to their over-expression in cancer lesions, some of these genes are upregulated in the presumably histo-pathological normal adjacent tissues. Of particular interest is clone G30CC that has been identified to be the gene that encodes S12 ribosomal protein. When employed for RNA–RNA in situ hybridization experiments, expression of G30CC could be detected in the immature basal epithelial cells of histo-pathological normal tissues collected from cervical cancer patients of early FIGO stages. In comparison, the expression of G30CC was not detected in cervical tissues collected from patients admitted for surgery of non-malignant conditions. These results allow the distinct possibility of employing the ribosomal protein S12 gene as an early molecular diagnostic identifier for the screening of human cervical cancer and a potential target employed for cancer gene therapy trials

Arousal of Cancer-Associated Stroma: Overexpression of Palladin Activates Fibroblasts to Promote Tumor Invasion

Background: Cancer-associated fibroblasts, comprised of activated fibroblasts or myofibroblasts, are found in the stroma surrounding solid tumors. These myofibroblasts promote invasion and metastasis of cancer cells. Mechanisms regulating the activation of the fibroblasts and the initiation of invasive tumorigenesis are of great interest. Upregulation of the cytoskeletal protein, palladin, has been detected in the stromal myofibroblasts surrounding many solid cancers and in expression screens for genes involved in invasion. Using a pancreatic cancer model, we investigated the functional consequence of overexpression of exogenous palladin in normal fibroblasts in vitro and its effect on the early stages of tumor invasion. Principal Findings: Palladin expression in stromal fibroblasts occurs very early in tumorigenesis. In vivo, concordant expression of palladin and the myofibroblast marker, alpha smooth muscle actin (a-SMA), occurs early at the dysplastic stages in peri-tumoral stroma and progressively increases in pancreatic tumorigenesis. In vitro introduction of exogenous 90 kD palladin into normal human dermal fibroblasts (HDFs) induces activation of stromal fibroblasts into myofibroblasts as marked by induction of a-SMA and vimentin, and through the physical change of cell morphology. Moreover, palladin expression in the fibroblasts enhances cellular migration, invasion through the extracellular matrix, and creation of tunnels through which cancer cells can follow. The fibroblast invasion and creation of tunnels results from the development o

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting

Suicide risk in schizophrenia: learning from the past to change the future

Suicide is a major cause of death among patients with schizophrenia. Research indicates that at least 5–13% of schizophrenic patients die by suicide, and it is likely that the higher end of range is the most accurate estimate. There is almost total agreement that the schizophrenic patient who is more likely to commit suicide is young, male, white and never married, with good premorbid function, post-psychotic depression and a history of substance abuse and suicide attempts. Hopelessness, social isolation, hospitalization, deteriorating health after a high level of premorbid functioning, recent loss or rejection, limited external support, and family stress or instability are risk factors for suicide in patients with schizophrenia. Suicidal schizophrenics usually fear further mental deterioration, and they experience either excessive treatment dependence or loss of faith in treatment. Awareness of illness has been reported as a major issue among suicidal schizophrenic patients, yet some researchers argue that insight into the illness does not increase suicide risk. Protective factors play also an important role in assessing suicide risk and should also be carefully evaluated. The neurobiological perspective offers a new approach for understanding self-destructive behavior among patients with schizophrenia and may improve the accuracy of screening schizophrenics for suicide. Although, there is general consensus on the risk factors, accurate knowledge as well as early recognition of patients at risk is still lacking in everyday clinical practice. Better knowledge may help clinicians and caretakers to implement preventive measures. This review paper is the results of a joint effort between researchers in the field of suicide in schizophrenia. Each expert provided a brief essay on one specific aspect of the problem. This is the first attempt to present a consensus report as well as the development of a set of guidelines for reducing suicide risk among schizophenia patients

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group.

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: National Center for Research Resources under award number 1 C06 RR12463-01, VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.Funder: Susan G Komen Foundation (CCR CCR18547966) and a Young Investigator Grant from the Breast Cancer Alliance.Funder: The Canadian Cancer SocietyFunder: Breast Cancer Research Foundation (BCRF), Grant No. 17-194Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring