Bright-field <i>in situ</i> hybridization detects gene alterations and viral infections useful for personalized management of cancer patients

<p><b>Introduction</b>: Bright-field <i>in situ</i> hybridization (ISH) methods detect gene alterations that may improve diagnostic precision and personalized management of cancer patients.</p> <p><b>Areas covered</b>: This review focuses on some bright-field ISH techniques for detection of gene amplification or viral infection that have already been introduced in tumor pathology, research and diagnostic practice. Other emerging ISH methods, for the detection of translocation, mRNA and microRNA have recently been developed and need both an optimization and analytical validation. The review also deals with their clinical applications and implications on the management of cancer patients.</p> <p><b>Expert commentary</b>: The technology of bright-field ISH applications has advanced significantly in the last decade. For example, an automated dual-color assay was developed as a clinical test for selecting cancer patients that are candidates for personalized therapy. Recently an emerging bright-field gene-protein assay has been developed. This method simultaneously detects the protein, gene and centromeric targets in the context of tissue morphology, and might be useful in assessing the <i>HER2</i> status particularly in equivocal cases or samples with heterogeneous tumors. The application of bright-field ISH methods has become the gold standard for the detection of tumor-associated viral infection as diagnostic or prognostic factors.</p

Overall Survival in overall population and based on type of studies.

<p>Overall Survival in overall population and based on type of studies.</p

Flowchart of search process.

<p>Flowchart of search process.</p

Overall Survival by type of therapy in patients with ECOG performance status of 0.

<p>Overall Survival by type of therapy in patients with ECOG performance status of 0.</p

Chemotherapy or Targeted Therapy as Second-Line Treatment of Advanced Gastric Cancer. A Systematic Review and Meta-Analysis of Published Studies

<div><p>Chemotherapy is a cornerstone in treatments of gastric cancer, but despite its benefit, less than 60% of patients receive salvage therapy in clinical practice. We performed a systematic review and meta-analysis based on trial data on the role of second-line treatment of advanced gastric cancer. MEDLINE/PubMed and Cochrane Library were searched for randomized phase III trials that compared active therapy to best supportive care in advanced gastric cancer. Data extraction was conducted according to the PRISMA statement. Summary HR for OS was calculated using a hierarchical Bayesian model and subgroup analysis was performed based on baseline Eastern Cooperative Oncology Group Performance Status (ECOG) performance status (0 vs. 1 or more). A total of 1,407 patients were evaluable for efficacy, 908 were treated in the experimental arms, with chemotherapy (231 pts) or with targeted therapies (677 pts). The risk of death was decreased by 18% (HR = 0.82; 95% CI, 0.79–0.85; posterior probability HR≥1: <0.00001) with active therapies. Chemotherapy and ramucirumab were able to decrease this risk by 27% and 22%, respectively. No differences were found between chemotherapy and ramucirumab. In patients with ECOG = 0 a greater benefit was found for chemotherapy with a reduction of the risk of death by 43% and no benefits were found for ramucirumab or everolimus. In patients with ECOG = 1 or more a significant reduction of the risk of death by 32% was reported in patients treated with ramucirumab, even if no significant difference was reported between chemotherapy and ramucirumab. This analysis reports that active and available therapies are able to prolong survival in patients with advanced gastric cancer with a different outcome based on initial patient’s performance status. New trials based on a better patient stratification are awaited.</p></div

Overall Survival by type of therapy in patients with ECOG performance status of 1 or more.

<p>Overall Survival by type of therapy in patients with ECOG performance status of 1 or more.</p

sj-docx-2-tam-10.1177_17588359241231259 – Supplemental material for Adjuvant and neoadjuvant chemotherapy for MSI early gastric cancer: a systematic review and meta-analysis

Supplemental material, sj-docx-2-tam-10.1177_17588359241231259 for Adjuvant and neoadjuvant chemotherapy for MSI early gastric cancer: a systematic review and meta-analysis by Fausto Petrelli, Maria Antista, Francesca Marra, Fulvia Milena Cribiu’, Valentina Rampulla, Filippo Pietrantonio, Lorenzo Dottorini, Michele Ghidini, Andrea Luciani, Alberto Zaniboni and Gianluca Tomasello in Therapeutic Advances in Medical Oncology</p

Flow-chart of patients population.

<p>Flow-chart of patients population.</p

sj-docx-1-tam-10.1177_17588359241231259 – Supplemental material for Adjuvant and neoadjuvant chemotherapy for MSI early gastric cancer: a systematic review and meta-analysis

Supplemental material, sj-docx-1-tam-10.1177_17588359241231259 for Adjuvant and neoadjuvant chemotherapy for MSI early gastric cancer: a systematic review and meta-analysis by Fausto Petrelli, Maria Antista, Francesca Marra, Fulvia Milena Cribiu’, Valentina Rampulla, Filippo Pietrantonio, Lorenzo Dottorini, Michele Ghidini, Andrea Luciani, Alberto Zaniboni and Gianluca Tomasello in Therapeutic Advances in Medical Oncology</p

ALK FISH examples.

<p>Gain of ALK GCN (including both low and high genomic gain) was defined as a mean of 3 to 5 fusion signals in ≥10% of cells (Figure on right). Disomic cells are shown in Figure on left.</p