Concurrent loss of MLH1, PMS2 and MSH6 immunoexpression in digestive system cancers indicating a widespread dysregulation in DNA repair processes

Immunohistochemical analysis of mismatch repair (MMR) protein expression is widely used to identify tumors with a deficient MMR (dMMR). MMR proteins (MLH1/PMS2 and MSH2/MSH6) work as functional heterodimers, which usually leads to the loss of expression in only one functional MMR heterodimer. Recently, there have been studies showing the simultaneous loss of immunoexpression in proteins of both heterodimers. Yet, this phenomenon has been rarely investigated. In this study, we retrospectively considered cases of different digestive system cancers (gastric cancer, ampullary cancer, small bowel cancer, colorectal cancer), which were immunohistochemically tested for dMMR within a 4-year period at our university hospital (n=352). Of the 103 cases showing dMMR, 5 cases (1.4% of all, 5.1% of dMMR cases) showed a concurrent loss of MLH1, PMS2 and MSH6 immunoexpression, whereas in the other 98 dMMR cases only one MMR heterodimer was affected. MLH1-/PMS2-/MSH6- cancer cases almost arose throughout the entire digestive tract: from the gastric antrum to the left colic flexur. To provide a comprehensive molecular characterization of this MLH1-/PMS2-/MSH6- immunophenotype, tumors were analyzed for microsatellite instability, MLH1 promotor hypermethylation and BRAF exon 15 status. Furthermore, we performed next-generation sequencing focusing on genes related to DNA repair. Here, we could detect pathogenic germline variants as well as multiple sporadic mutations in different genes involved in MMR and homologous recombination repair (HRR) respectively. The affected MMR/HRR-related genes were: ATM, BARD1, BRCA1, CDK12, CHEK1, CHEK2, FANCA, MLH1, MSH6, PALB2, TP53. Considering the biologic function of HRR/MMR proteins as potential drug targets and the low frequency of most of these mutations in digestive system cancers in general, their common occurrence in our MLH1-/PMS2-/MSH6- cases seems to be even more noteworthy, highlighting the need for recognition, awareness and further investigation of this unusual IHC staining pattern

Deep learning trained on lymph node status predicts outcome from gastric cancer histopathology: a retrospective multicentric study

Aim Gastric cancer (GC) is a tumor entity with highly variant outcomes. Lymph node metastasis is a prognostically adverse biomarker. We hypothesized that GC primary tissue contains information that is predictive of lymph node status and patient prognosis and that this information can be extracted using Deep Learning (DL). Methods Using three patient cohorts comprising 1146 patients, we trained and validated a DL system to predict lymph node status directly from hematoxylin-and-eosin stained GC tissue sections. We investigated the concordance between the DL-based prediction from the primary tumor slides (aiN score) and the histopathological lymph node status (pN). Furthermore, we assessed the prognostic value of the aiN score alone and when combined with the pN status. Results The aiN score predicted the pN status reaching Area Under the Receiver Operating Characteristic curves (AUROCs) of 0.71 in the training cohort and 0.69 and 0.65 in the two test cohorts. In a multivariate Cox analysis, the aiN score was an independent predictor of patient survival with Hazard Ratios (HR) of 1.5 in the training cohort and of 1.3 and 2.2 in the two test cohorts. A combination of the aiN score and the pN status prognostically stratified patients by survival with p-values <0.05 in log-rank tests. Conclusion GC primary tumor tissue contains additional prognostic information that is accessible using the aiN score. In combination with the pN status, this can be used for personalized management of gastric cancer patients after prospective validation

Monocyte activation by serum extracellular vesicles from Parkinson’s disease patients

Peripheral inflammation and neuroinflammation can result in neurodegeneration and parkinsonism. There is recent evidence that immune responses – especially monocytic cytokine secretion patterns – in Parkinson’s Disease (PD) patients are dysregulated. It is known that serum extracellular vesicles (EVs) can induce proinflammatory reactions of immune cells. Moreover, PD EVs seem to carry an altered cargo – specifically containing higher levels of α-synuclein. Interestingly, α-synuclein pathology seems to act synergistically with monocytic dysregulation in PD to trigger excessive inflammatory responses. As it is known that monocytes can contribute to PD neurodegeneration and immune dysregulation plays an early event in PD, we investigated the predisposition of primary human monocytes of healthy donors to pathologic PD serum EVs by assessing release of proinflammatory interleukin-6 (IL-6) upon EV exposure. We isolated serum EVs of healthy controls (HCs) and PD patients by differential ultracentrifugation (UC) and checked the quality and purity of our EVs by Nanoparticle Tracking Analysis (NTA) and Western Blot (WB). NTA as well as WB proved our EV isolation protocol to be not only effective but also providing high purity. Prior to treatment, we isolated human monocytes of young as well as aged healthy donors by positive, CD14-based selection of monocytes from peripheral blood mononuclear cells. Monocytes were then stimulated with lipopolysaccharide (LPS) as a positive control and with HC EVs as well as with PD EVs. To rule out any unspecific activation of monocytes during isolation or cultivation and to quantify basal IL-6 release, negative controls with only unconditioned media were performed. We could show that treatment with pooled HC and PD EVs results in an inflammatory activation of young as well as aged human monocytes. The activation shows widespread interindividual differences. We also found that young monocytes seem to be more suitable for detecting slight changes in cytokine secretion as they show a more distinct cytokine secretion pattern. Young monocytes react to triggers such as LPS with a higher increase in IL-6 secretion but show a lower basal cytokine secretion rate than aged monocytes. Most importantly, we could demonstrate that there is a predisposition of some healthy donors’ monocytes to react excessively to PD EVs. Our findings indicate that this predisposition is more likely to be enriched in young healthy donors’ monocytes than in those of aged healthy individuals. On average, no differences in monocytic activation upon stimulation with HC and PD EVs could be observed – neither in young nor in aged monocytes. Furthermore, we could show that monocytic activation by HC as well as PD EVs is not only influenced by monocytic vulnerability but also by the composition of EVs. Stimulating young healthy donors’ monocytes with individual EVs showed that EVs that can increase cytokine secretion in one donor do not necessarily boost another donors’ immune response. The opposite may be even the case as we could show that some donors’ EVs do not influence or even inhibit monocytic IL-6 release. Taken together, our data suggest that there are indeed ‘responders’ among healthy individuals to pathologic PD EVs as some healthy donors’ monocytes seemingly reacted to PD EVs with an increased IL-6 release. Additionally, our data prompt that pathologic PD EVs and dysregulation of PD monocytes could potentiate each other and could play a detrimental role in initiating and maintaining neuroinflammatory processes in PD

Alterations in natural killer cells in colorectal cancer patients with Stroma AReactive Invasion Front Areas (SARIFA)

Recently, our group introduced Stroma AReactive Invasion Front Areas (SARIFA) as an independent prognostic predictor for a poorer outcome in colon cancer patients, which is probably based on immunologic alterations combined with a direct tumor-adipocyte interaction: the two together reflecting a distinct tumor biology. Considering it is already known that peripheral immune cells are altered in colorectal cancer (CRC) patients, this study aims to investigate the changes in lymphocyte subsets in SARIFA-positive cases and correlate these changes with the local immune response. Methods: Flow cytometry was performed to analyze B, T, and natural killer (NK) cells in the peripheral blood (PB) of 45 CRC patients. Consecutively, lymphocytes in PB, tumor-infiltrating lymphocytes (TILs), and CD56+ and CD57+ lymphocytes at the invasion front and the tumor center were compared between patients with SARIFA-positive and SARIFA-negative CRCs. Results: Whereas no differences could be observed regarding most PB lymphocyte populations as well as TILs, NK cells were dramatically reduced in the PB of SARIFA-positive cases. Moreover, CD56 and CD57 immunohistochemistry suggested SARIFA-status-dependent changes regarding NK cells and NK-like lymphocytes in the tumor microenvironment. Conclusion: This study proves that our newly introduced biomarker, SARIFA, comes along with distinct immunologic alterations, especially regarding NK cells

Deep learning for dual detection of microsatellite instability and POLE mutations in colorectal cancer histopathology

Abstract In the spectrum of colorectal tumors, microsatellite-stable (MSS) tumors with DNA polymerase ε (POLE) mutations exhibit a hypermutated profile, holding the potential to respond to immunotherapy similarly to their microsatellite-instable (MSI) counterparts. Yet, due to their rarity and the associated testing costs, systematic screening for these mutations is not commonly pursued. Notably, the histopathological phenotype resulting from POLE mutations is theorized to resemble that of MSI. This resemblance not only could facilitate their detection by a transformer-based Deep Learning (DL) system trained on MSI pathology slides, but also indicates the possibility for MSS patients with POLE mutations to access enhanced treatment options, which might otherwise be overlooked. To harness this potential, we trained a Deep Learning classifier on a large dataset with the ground truth for microsatellite status and subsequently validated its capabilities for MSI and POLE detection across three external cohorts. Our model accurately identified MSI status in both the internal and external resection cohorts using pathology images alone. Notably, with a classification threshold of 0.5, over 75% of POLE driver mutant patients in the external resection cohorts were flagged as “positive” by a DL system trained on MSI status. In a clinical setting, deploying this DL model as a preliminary screening tool could facilitate the efficient identification of clinically relevant MSI and POLE mutations in colorectal tumors, in one go