In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

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The American Joint Committee on Cancer/Union Internationale Contre le Cancer (AJCC/UICC) TNM staging system provides the most reliable guidelines for the routine prognostication and treatment of colorectal carcinoma. This traditional tumour staging summarizes data on tumour burden (T), the presence of cancer cells in draining and regional lymph nodes (N) and evidence for distant metastases (M). However, it is now recognized that the clinical outcome can vary significantly among patients within the same stage. The current classification provides limited prognostic information and does not predict response to therapy. Multiple ways to classify cancer and to distinguish different subtypes of colorectal cancer have been proposed, including morphology, cell origin, molecular pathways, mutation status and gene expression-based stratification. These parameters rely on tumour-cell characteristics. Extensive literature has investigated the host immune response against cancer and demonstrated the prognostic impact of the in situ immune cell infiltrate in tumours. A methodology named ‘Immunoscore’ has been defined to quantify the in situ immune infiltrate. In colorectal cancer, the Immunoscore may add to the significance of the current AJCC/UICC TNM classification, since it has been demonstrated to be a prognostic factor superior to the AJCC/UICC TNM classification. An international consortium has been initiated to validate and promote the Immunoscore in routine clinical settings. The results of this international consortium may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune). © 2013 The Authors. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Autophagy is a homeostatic, catabolic degradation process whereby cellular proteins and organelles are engulfed into autophagosomes, digested in lysosomes and recycled to sustain cellular metabolism. Autophagy has dual roles in cancer, acting as both a tumor suppressor by preventing the accumulation of damaged proteins and organelles and as a mechanism of cell survival that can promote the growth of established tumors. Tumor cells activate autophagy in response to cellular stress including hypoxia and increased metabolic demands related to rapid cell proliferation. Autophagy-related stress tolerance can enable cell survival by maintaining energy production that can lead to tumor growth and therapeutic resistance, as shown in preclinical models where the inhibition of autophagy can restore chemosensitivity and enhance tumor cell death. These results established autophagy as a therapeutic target and have led to multiple early phase clinical trials in humans evaluating autophagy inhibition using hydroxychloroquine in combination with chemotherapy or targeted agents. Targeting autophagy in cancer provides new opportunities for drug development since more potent and specific inhibitors of autophagy are needed. The role of autophagy and its regulation in cancer cells continues to emerge and studies aim to define optimal strategies to modulate autophagy for therapeutic advantage.

Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the ‘Immunoscore’ into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).

Tumor mutational burden (TMB), defi ned as the number of somatic mutations per megabase of interrogated genomic sequence, varies across malignancies. Panel sequencing-based estimates of TMB have largely replaced whole-exome sequencing-derived TMB in the clinic. Retrospective evidence suggests that TMB can predict the effi cacy of immune checkpoint inhibitors, and data from KEYNOTE-158 led to the recent FDA approval of pembrolizumab for the TMBhigh tumor subgroup. Unmet needs include prospective validation of TMB cutoffs in relationship to tumor type and patient outcomes. Furthermore, standardization and harmonization of TMB measurement across test platforms are important to the successful implementation of TMB in clinical practice.Signifi cance: Evaluation of TMB as a predictive biomarker creates the need to harmonize panel-based TMB estimation and standardize its reporting. TMB can improve the predictive accuracy for immunotherapy outcomes, and has the potential to expand the candidate pool of patients for treatment with immune checkpoint inhibitors. Responses were observed across tumor types, and microsatellite instability-high (MSI-H) status did not account for all of the increased clinical benefi t in the TMB-high subgroup ( 24 ).On the basis of these data, the FDA approved pembrolizumab monotherapy for the subgroup of solid-tumor patients with TMB ≥10 mut/Mb who are treatment-refractory and lack satisfactory alternative treatment options. Although data from KEYNOTE-158 demonstrated a role for TMB in selection of patients for cancer treatment, important issues remain,

Patients with dMMR colon cancers have reduced rates of tumor recurrence, delayed TTR, and improved survival rates, compared with pMMR colon cancers. Distant recurrences were reduced by 5-FU-based adjuvant treatment in dMMR stage III tumors, and a subset analysis suggested that any treatment benefit was restricted to suspected germline vs sporadic tumors.

Background and Aims. Colorectal cancer (CRC) is a heterogeneous disease that can develop via several pathways. Different CRC subtypes, identified based on tumor markers, have been proposed to reflect these pathways. We evaluated the significance of these previously proposed classifications to survival. Methods. Participants in the population-based Seattle Colon Cancer Family Registry were diagnosed with invasive CRC from 1998 through 2007 in western Washington State (n=2706), and followed for survival through 2012. Tumor samples were collected from 2050 participants and classified into 5 subtypes based on combinations of tumor markers: type 1 (microsatellite instability [MSI] high, CpG island methylator phenotype [CIMP] positive, positive for BRAF mutation, negative for KRAS mutation); type 2 (microsatellite stable [MSS] or MSI-low, CIMP-positive, positive for BRAF mutation, negative for KRAS mutation); type 3 (MSS or MSI-low, non-CIMP, negative for BRAF mutation, positive for KRAS mutation); type 4 (MSS or MSI-low, non-CIMP, negative for mutations in BRAF and KRAS); and type 5 (MSI-high, non-CIMP, negative for mutations in BRAF and KRAS). Multiple imputation was used to impute tumor markers for those missing data on 1-3 markers. We used Cox regression to estimate hazard ratios (HR) and 95% confidence intervals (CI) for associations of subtypes with disease-specific and overall mortality, adjusting for age, sex, body mass, diagnosis year, and smoking history. Results. Compared to participants with type 4 tumors (the most predominant), participants with type 2 tumors had the highest disease-specific mortality (HR=2.20, 95% CI: 1.47-3.31); subjects with type 3 tumors also had higher disease-specific mortality (HR=1.32, 95% CI: 1.07-1.63). Subjects with type 5 tumors had the lowest disease-specific mortality (HR=0.30, 95% CI: 0.14-0.66). Associations with overall mortality were similar to those with disease-specific mortality. Conclusions. Based on a large, population-based study, CRC subtypes, defined by proposed etiologic pathways, are associated with marked differences in survival. These findings indicate the clinical importance of studies into the molecular heterogeneity of CRC.