SARIFA as a new histopathological biomarker is associated with adverse clinicopathological characteristics, tumor-promoting fatty-acid metabolism, and might predict a metastatic pattern in pT3a prostate cancer.

BACKGROUND: Recently, we introduced Stroma-AReactive-Invasion-Front-Areas (SARIFA) as a novel hematoxylin-eosin (H&E)-based histopathologic prognostic biomarker for various gastrointestinal cancers, closely related to lipid metabolism. To date, no studies on SARIFA, which is defined as direct tumor-adipocyte-interaction, beyond the alimentary tract exist. Hence, the objective of our current investigation was to study the significance of SARIFA in pT3a prostate cancer (PCa) and explore its association with lipid metabolism in PCa as lipid metabolism plays a key role in PCa development and progression. METHODS: To this end, we evaluated SARIFA-status in 301 radical prostatectomy specimens and examined the relationship between SARIFA-status, clinicopathological characteristics, overall survival, and immunohistochemical expression of FABP4 and CD36 (proteins closely involved in fatty-acid metabolism). Additionally, we investigated the correlation between SARIFA and biochemical recurrence-free survival (BRFS) and PSMA-positive recurrences in PET/CT imaging in a patient subgroup. Moreover, a quantitative SARIFA cut-off was established to further understand the underlying tumor biology. RESULTS: SARIFA positivity occurred in 59.1% (n = 178) of pT3a PCas. Our analysis demonstrated that SARIFA positivity is strongly associated with established high-risk features, such as R1 status, extraprostatic extension, and higher initial PSA values. Additionally, we observed an upregulation of immunohistochemical CD36 expression specifically at SARIFAs (p = 0.00014). Kaplan-Meier analyses revealed a trend toward poorer outcomes, particularly in terms of BRFS (p = 0.1). More extensive tumor-adipocyte interaction, assessed as quantity-dependent SARIFA-status on H&E slides, is also significantly associated with high-risk features, such as lymph node metastasis, and seems to be associated with worse survival outcomes (p = 0.16). Moreover, SARIFA positivity appeared to be linked to more distant lymph node and bone metastasis, although statistical significance was slightly not achieved (both p > 0.05). CONCLUSIONS: This is the first study to introduce SARIFA as easy-and-fast-to-assess H&E-based biomarker in locally advanced PCa. SARIFA as the histopathologic correlate of a distinct tumor biology, closely related to lipid metabolism, could pave the way to a more detailed patient stratification and to the development of novel drugs targeting lipid metabolism in pT3a PCa. On the basis of this biomarker discovery study, further research efforts on the prognostic and predictive role of SARIFA in PCa can be designed.

Novel biomarker SARIFA in colorectal cancer: highly prognostic, not genetically driven and histologic indicator of a distinct tumor biology.

SARIFA (Stroma AReactive Invasion Front Areas) has recently emerged as a promising histopathological biomarker for colon and gastric cancer. To elucidate the underlying tumor biology, we assessed SARIFA-status in tissue specimens from The-Cancer-Genome-Atlas (TCGA) cohorts COAD (colonic adenocarcinoma) and READ (rectal adenocarcinoma). For the final analysis, 207 CRC patients could be included, consisting of 69 SARIFA-positive and 138 SARIFA-negative cases. In this external validation cohort, H&E-based SARIFA-positivity was strongly correlated with unfavorable overall, disease-specific, and progression-free survival, partly outperforming conventional prognostic factors. SARIFA-positivity was not associated with known high-risk genetic profiles, such as BRAF V600E mutations or microsatellite-stable status. Transcriptionally, SARIFA-positive CRCs exhibited an overlap with CRC consensus molecular subtypes CMS1 and CMS4, along with distinct differential gene expression patterns, linked to lipid metabolism and increased stromal cell infiltration scores (SIIS). Gene-expression-based drug sensitivity prediction revealed a differential treatment response in SARIFA-positive CRCs. In conclusion, SARIFA represents the H&E-based counterpart of an aggressive tumor biology, demonstrating a partial overlap with CMS1/4 and also adding a further biological layer related to lipid metabolism. Our findings underscore SARIFA-status as an ideal biomarker for refined patient stratification and novel drug developments, particularly given its cost-effective assessment based on routinely available H&E slides.

Stroma AReactive Invasion Front Areas (SARIFA) proves prognostic relevance in gastric carcinoma and is based on a tumor-adipocyte interaction indicating an altered immune response.

BACKGROUND: Recently, we presented Stroma AReactive Invasion Front Areas (SARIFA) as a new histomorphologic negative prognostic biomarker in gastric cancer. It is defined as direct contact between tumor cells and fat cells. The aim of this study was to further elucidate the underlying genomic, transcriptional, and immunological mechanisms of the SARIFA phenomenon. METHODS: To address these questions, SARIFA was classified on H&E-stained tissue sections of three cohorts: an external cohort (n = 489, prognostic validation), the TCGA-STAD cohort (n = 194, genomic and transcriptomic analysis), and a local cohort (n = 60, digital spatial profiling (whole transcriptome) and double RNA in situ hybridization/immunostaining of cytokines). RESULTS: SARIFA status proved to be an independent negative prognostic factor for overall survival in an external cohort of gastric carcinomas. In TCGA-STAD cohort, SARIFA is not driven by distinct genomic alterations, whereas the gene expression analyses showed an upregulation of FABP4 in SARIFA-positive tumors. In addition, the transcriptional regulations of white adipocyte differentiation, triglyceride metabolism, and catabolism were upregulated in pathway analyses. In the DSP analysis of SARIFA-positive tumors, FABP4 and the transcriptional regulation of white adipocyte differentiation were upregulated in macrophages. Additionally, a significantly lower expression of the cytokines IL6 and TNFα was observed at the invasion front. CONCLUSIONS: SARIFA proves to be a strong negative prognostic biomarker in advanced gastric cancer, implicating an interaction of tumor cells with tumor-promoting adipocytes with crucial changes in tumor cell metabolism. SARIFA is not driven by tumor genetics but is very likely driven by an altered immune response as a causative mechanism.

Stroma AReactive Invasion Front Areas (SARIFA) improves prognostic risk stratification of perioperative chemotherapy treated oesophagogastric cancer patients from the MAGIC and the ST03 trial.

BACKGROUND: Tumour-associated fat cells without desmoplastic stroma reaction at the invasion front (Stroma AReactive Invasion Front Areas (SARIFA)) is a prognostic biomarker in gastric and colon cancer. The clinical utility of the SARIFA status in oesophagogastric cancer patients treated with perioperative chemotherapy is currently unknown. METHODS: The SARIFA status was determined in tissue sections from patients recruited into the MAGIC (n = 292) or ST03 (n = 693) trials treated with surgery alone (S, MAGIC) or perioperative chemotherapy (MAGIC, ST03). The relationship between SARIFA status, clinicopathological factors, overall survival (OS) and treatment was analysed. RESULTS: The SARIFA status was positive in 42% MAGIC trial S patients, 28% MAGIC and 48% ST03 patients after pre-operative chemotherapy. SARIFA status was related to OS in MAGIC trial S patients and was an independent prognostic biomarker in ST03 trial patients (HR 1.974, 95% CI 1.555-2.507, p < 0.001). ST03 patients with lymph node metastasis (ypN + ) and SARIFA-positive tumours had poorer OS than patients with ypN+ and SARIFA-negative tumours (plogrank < 0.001). CONCLUSIONS: The SARIFA status has clinical utility as prognostic biomarker in oesophagogastric cancer patients irrespective of treatment modality. Whilst underlying biological mechanisms warrant further investigation, the SARIFA status might be used to identify new drug targets, potentially enabling repurposing of existing drugs targeting lipid metabolism.

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

AIM: Gastric cancer (GC) is a tumour entity with highly variant outcomes. Lymph node metastasis is a prognostically adverse biomarker. We hypothesised 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 haematoxylin and eosin-stained GC tissue sections. We investigated the concordance between the DL-based prediction from the primary tumour 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 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 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 logrank tests. CONCLUSION: GC primary tumour tissue contains additional prognostic information that is accessible using the aiN score. In combination with the pN status, this can be used for personalised management of GC patients after prospective validation.

Alterations in Natural Killer Cells in Colorectal Cancer Patients with Stroma AReactive Invasion Front Areas (SARIFA).

BACKGROUND: 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.

Arthroscopic rod technique compared to stress ultrasound in the dynamic evaluation of lateral ligament instabilities of the elbow.

INTRODUCTION: The purpose was to compare the arthroscopic rod technique to stress ultrasound in the dynamic assessment of lateral elbow instabilities. MATERIALS AND METHODS: Fifteen elbows of eight specimen with a mean age of 66.4 ± 13.3 years were assessed in a prone position following a defined dissection setup. After evaluation of the native status, an arthroscopic dissection of the radial collateral ligament (RCL) or lateral ulnar collateral ligament (LUCL), and finally of entire capsuloligamentous structures was performed. Three raters examined each state (native, RCL or LUCL lesion, complete lesion) with the arthroscopic rod technique in 90° flexion and with stress ultrasound in 30 and 90° flexion. The intra-class correlation coefficient (ICC) was calculated to assess the interrater reliability as well as test-retest reliability for each testing modality (arthroscopy and ultrasound). RESULTS: The arthroscopic rod technique showed a superior interrater and test-retest reliability of 0.953 and 0.959 (P < 0.001), respectively, when compared to stress ultrasound with an ICC of 0.4 and 0.611 (P < 0.001). A joint space opening during arthroscopy of > 6 mm humero-ulnar or > 7 mm humero-radial was indicative for a lateral collateral ligament lesion. However, a differentiation between an isolated RCL or LUCL tear was not possible. A lateral joint opening of ≥ 9 mm was only observed in complete tears of the lateral capsuloligamentous complex. CONCLUSIONS: The arthroscopic rod technique showed a superior interrater and test-retest reliability when compared to stress ultrasound. Arthroscopic assessment for radial elbow instability was found to be reliable and reproducible. A joint gapping ≥ 9 mm in the arthroscopic evaluation is a sign for a complete insufficiency of the radial capsuloligamentous complex. However, it is not possible to precisely distinguish between a lesion of the RCL or LUCL by arthroscopy. On the basis of our results, dynamic ultrasound testing may be inappropriate to objectify lateral elbow instability.

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.

An artificial intelligence algorithm is highly accurate for detecting endoscopic features of eosinophilic esophagitis.

The endoscopic features associated with eosinophilic esophagitis (EoE) may be missed during routine endoscopy. We aimed to develop and evaluate an Artificial Intelligence (AI) algorithm for detecting and quantifying the endoscopic features of EoE in white light images, supplemented by the EoE Endoscopic Reference Score (EREFS). An AI algorithm (AI-EoE) was constructed and trained to differentiate between EoE and normal esophagus using endoscopic white light images extracted from the database of the University Hospital Augsburg. In addition to binary classification, a second algorithm was trained with specific auxiliary branches for each EREFS feature (AI-EoE-EREFS). The AI algorithms were evaluated on an external data set from the University of North Carolina, Chapel Hill (UNC), and compared with the performance of human endoscopists with varying levels of experience. The overall sensitivity, specificity, and accuracy of AI-EoE were 0.93 for all measures, while the AUC was 0.986. With additional auxiliary branches for the EREFS categories, the AI algorithm (AI-EoE-EREFS) performance improved to 0.96, 0.94, 0.95, and 0.992 for sensitivity, specificity, accuracy, and AUC, respectively. AI-EoE and AI-EoE-EREFS performed significantly better than endoscopy beginners and senior fellows on the same set of images. An AI algorithm can be trained to detect and quantify endoscopic features of EoE with excellent performance scores. The addition of the EREFS criteria improved the performance of the AI algorithm, which performed significantly better than endoscopists with a lower or medium experience level.

High viral loads: what drives fatal cases of COVID-19 in vaccinees? - an autopsy study.

The rate of SARS-CoV-2 infections in vaccinees has become a relevant serious issue. This study aimed to determine the causes of death, histological organ alteration, and viral spread in relation to demographic, clinical-pathological, viral variants, and vaccine types for deceased individuals with proven SARS-CoV-2 infection after vaccination who died between January and November 2021. Twenty-nine consecutively collected cases were analyzed and compared to 141 nonvaccinated control cases. Autopsies were performed on 16 partially and 13 fully vaccinated individuals. Most patients were elderly and suffered from several relevant comorbidities. Real-time RT-PCR (RT-qPCR) identified a significantly increased rate of generalized viral dissemination within organ systems in vaccinated cases versus nonvaccinated cases (45% vs. 16%, respectively; P = 0.008) mainly with Ct-values of higher than 25 in non-respiratory samples. However, vaccinated cases also showed high viral loads, reaching Ct-values below 10, especially in the upper airways and lungs. This was accompanied by high rates of pulmonal bacterial or mycotic superinfections and the occurrence of immunocompromising factors, such as malignancies, immunosuppressive drug intake, or decreased immunoglobulin levels. All these findings were particularly accentuated in partially vaccinated patients compared to fully vaccinated individuals. The virus dissemination observed in our case study may indicate that patients with an impaired immune system have a decreased ability to eliminate the virus. However, the potential role of antibody-dependent enhancement must also be ruled out in future studies. Fatal cases of COVID-19 in vaccinees were rare and often associated with severe comorbidities or other immunosuppressive conditions.

IgG4-related pseudotumours: a series of 12 cases and a review of the literature.

IgG4-related pseudotumours (IgG4-RPT) represent a distinctive manifestation in the broad spectrum of IgG4-related diseases (IgG4-RD). Due to their wide morphology and rarity, IgG4-RPTs represent a diagnostic challenge in the differential between reactive lesions and a fibrous soft tissue tumours. Thus, our aim was to characterise our cases and review the literature, focusing on the macroscopic and microscopic features of the lesions. In this paper, we summarise the possible presentations and histomorphological features of IgG4-RPT based on data collected from the literature and from cases at our institute and provide an overview of the pathogenesis and histological characteristics based on the knowledge accumulated in recent years. We collected surgical cases with a diagnosis of IgG4-RPT over the period 2013-2020 at two centres and analysed their macroscopic, histological, and immunohistochemical profiles. Furthermore, we performed a literature research in the MEDLINE and EBSCO databases regarding case reports and studies with the explicit diagnosis of IgG4-RPT. Our cases consist of nine men and three women, with an average age of 60±14 years, representing about 0.05% of the lesions evaluated at the two departments. The involved sites include the kidney, lung, gallbladder, pterygopalatine fossa, spleen, tongue, mediastinum, and submandibular gland. Grossly, nine lesions showed sharp margins. On histological examination, all the lesions showed an abundant inflammatory infiltrate with lymphocytes and IgG4-positive plasma cells as well as characteristic fibroblastic storiform proliferation. The literature search revealed 266 cases and similar histomorphological features in 23 locations. In 30 of these cases (11%), IgG4-RPTs were multifocal. IgG4-RPT are exceedingly rare lesions, which makes them challenging to diagnose. They can affect different sites, and the histomorphological presentation may differ.

ALK, NUT, and TRK Do Not Play Relevant Roles in Gastric Cancer-Results of an Immunohistochemical Study in a Large Series.

ALK, NUT, and TRK are rare molecular aberrations that are pathognomonic for specific rare tumors. In low frequencies, however, they are found in a wide range of other tumor entities. This study aimed to investigate the frequency, association with clinicopathological characteristics, and prognosis of the immunohistochemical expressions of ALK, NUT, and TRK in 477 adenocarcinomas of the stomach and gastroesophageal junction. Seven cases (1.5%) showed an expression of TRK. In NGS, no NTRK fusion was confirmed. No case with ALK or NUT expression was detected. ALK, NUT, and NTRK expression does not seem to play an important role in gastric carcinomas.

Elevated microsatellite instability at selected tetranucleotide (EMAST) repeats in gastric cancer: a distinct microsatellite instability type with potential clinical impact?

We investigated the clinical impact of elevated microsatellite instability at selected tetranucleotide (EMAST) repeats in the context of neoadjuvant chemotherapy (CTx) in gastric/gastro-oesophageal adenocarcinomas. We analysed 583 resected tumours (272 without and 311 after CTx) and 142 tumour biopsies before CTx. If at least two or three of the five tetranucleotide repeat markers tested showed instability, the tumours were defined as EMAST (2+) or EMAST (3+), respectively. Expression of mismatch repair proteins including MSH3 was analysed using immunohistochemistry. Microsatellite instability (MSI) and Epstein-Barr virus (EBV) positivity were determined using standard assays. EMAST (2+) and (3+) were detected in 17.8 and 11.5% of the tumours, respectively. The frequency of EMAST (2+) or (3+) in MSI-high (MSI-H) tumours was 96.2 or 92.5%, respectively, demonstrating a high overlap with this molecular subtype, and the association of EMAST and MSI status was significant (each overall p < 0.001). EMAST (2+ or 3+) alone in MSI-H and EBV-negative tumours demonstrated only a statistically significant association of EMAST (2+) positivity and negative lymph node status (42.3% in EMAST (2+) and 28.8% in EMAST negative, p = 0.045). EMAST alone by neither definition was significantly associated with overall survival (OS) of the patients. The median OS for EMAST (2+) patients was 40.0 months (95% confidence interval [CI] 16.4-63.6) compared with 38.7 months (95% CI 26.3-51.1) for the EMAST-negative group (p = 0.880). The median OS for EMAST (3+) patients was 46.7 months (95% CI 18.2-75.2) and 38.7 months (95% CI 26.2-51.2) for the negative group (p = 0.879). No statistically significant association with response to neoadjuvant CTx was observed (p = 0.992 and p = 0.433 for EMAST (2+) and (3+), respectively). In conclusion, our results demonstrate a nearly complete intersection between MSI-H and EMAST and they indicate that EMAST alone is not a distinct instability type associated with noticeable clinico-pathological characteristics of gastric carcinoma patients.

Stroma AReactive Invasion Front Areas (SARIFA) - a new prognostic biomarker in gastric cancer related to tumor-promoting adipocytes.

Compared to other malignancies, there is a lack of easy-to-evaluate biomarkers for gastric cancer, which is associated with an adverse clinical outcome in many cases. Here, we present Stroma AReactive Invasion Front Areas (SARIFA) as a new histological prognostic marker. We defined SARIFA as the direct contact between a cluster of tumor glands/cells comprising at least five tumor cells and inconspicuous surrounding adipose tissue at the invasion front. A total of 480 adenocarcinomas of the stomach and the gastroesophageal junction from two different collections were classified according to SARIFA. To understand the potential underlying mechanisms, a transcriptome analysis was conducted using digital spatial profiling (DSP). It was found that 20% of the tumors were SARIFA-positive. Kappa values between the three pathologists were good in both collections: 0.74 and 0.78. Patients who presented SARIFA-positive tumors had a significantly lower overall survival in Collections A (median: 20.0 versus 44.0 months; p = 0.014, n = 160) and B (median: 15.0 versus 41.0 months; p < 0.0001, n = 320). SARIFA positivity emerged as a negative independent prognostic factor for overall survival (HR 1.638, 95% CI 1.153-2.326, p = 0.006). Using DSP, the most upregulated genes in SARIFA-positive cases were those associated with triglyceride catabolism and endogenous sterols. COL15A1, FABP2, and FABP4 were differentially expressed in positive cases. At the protein level, the expression of proteins related to lipid metabolism was confirmed. SARIFA combines low inter-observer variability, minimal effort, and high prognostic relevance, and is therefore an extremely promising biomarker related to tumor-promoting adipocytes in gastric cancer. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Impaired Dendritic Cell Homing in COVID-19.

The high mortality of COVID-19 is mostly attributed to acute respiratory distress syndrome (ARDS), whose histopathological correlate is diffuse alveolar damage (DAD). Furthermore, severe COVID-19 is often accompanied by a cytokine storm and a disrupted response of the adaptive immune system. Studies aiming to depict this dysregulation have mostly investigated the peripheral cell count as well as the functionality of immune cells. We investigated the impact of SARS-CoV-2 on antigen-presenting cells using multiplexed immunofluorescence. Similar to MERS-CoV and SARS-CoV, SARS-CoV-2 appears to be impairing the maturation of dendritic cells (DCs). DC maturation involves a switch in surface antigen expression, which enables the cells' homing to lymph nodes and the subsequent activation of T-cells. As quantitative descriptions of the local inflammatory infiltrate are still scarce, we compared the cell population of professional antigen-presenting cells (APC) in the lungs of COVID-19 autopsy cases in different stages of DAD. We found an increased count of myeloid dendritic cells (mDCs) in later stages. Interestingly, mDCs also showed no significant upregulation of maturation markers in DAD-specimens with high viral load. Accumulation of immature mDCs, which are unable to home to lymph nodes, ultimately results in an inadequate T-cell response.

Stroma AReactive Invasion Front Areas (SARIFA)-A New Easily to Determine Biomarker in Colon Cancer-Results of a Retrospective Study.

Many studies have used histomorphological features to more precisely predict the prognosis of patients with colon cancer, focusing on tumor budding, poorly differentiated clusters, and the tumor-stroma ratio. Here, we introduce SARIFA: Stroma AReactive Invasion Front Area(s). We defined SARIFA as the direct contact between a tumor gland/tumor cell cluster (≥5 cells) and inconspicuous surrounding adipose tissue in the invasion front. In this retrospective, single-center study, we classified 449 adipose-infiltrative adenocarcinomas (not otherwise specified) from two groups based on SARIFA and found 25% of all tumors to be SARIFA-positive. Kappa values between the two pathologists were good/very good: 0.77 and 0.87. Patients with SARIFA-positive tumors had a significantly shorter colon-cancer-specific survival (p = 0.008, group A), absence of metastasis, and overall survival (p < 0.001, p = 0.003, group B). SARIFA was significantly associated with adverse features such as pT4 stage, lymph node metastasis, tumor budding, and higher tumor grade. Moreover, SARIFA was confirmed as an independent prognostic indicator for colon-cancer-specific survival (p = 0.011, group A). SARIFA assessment was very quick (<1 min). Because of low interobserver variability and good prognostic significance, SARIFA seems to be a promising histomorphological prognostic indicator in adipose-infiltrative adenocarcinomas of the colon. Further studies should validate our results and also determine whether SARIFA is a universal prognostic indicator in solid cancers.

Diverse 'just-right' levels of chromosomal instability and their clinical implications in neoadjuvant treated gastric cancer.

BACKGROUND: The Cancer Genome Atlas (TCGA) consortium described EBV positivity(+), high microsatellite instability (MSI-H), genomic stability (GS) and chromosomal instability (CIN) as molecular subtypes in gastric carcinomas (GC). We investigated the predictive and prognostic value of these subtypes with emphasis on CIN in the context of neoadjuvant chemotherapy (CTx) in GC. METHODS: TCGA subgroups were determined for 612 resected adenocarcinomas of the stomach and gastro-oesophageal junction (291 without, 321 with CTx) and 143 biopsies before CTx. EBV and MSI-H were analysed by standard assays. CIN was detected by multiplex PCRs analysing 22 microsatellite markers. Besides the TCGA classification, CIN was divided into four CIN-subgroups: low, moderate, substantial, high. Mutation profiling was performed for 52 tumours by next-generation sequencing. RESULTS: EBV(+) (HR, 0.48; 95% CI, 0.23-1.02), MSI-H (HR, 0.56; 95% CI, 0.35-0.89) and GS (HR, 0.72; 95% CI, 0.45-1.13) were associated with increased survival compared to CIN in the resected tumours. Considering the extended CIN-classification, CIN-substantial was a negative prognostic factor in uni- and multivariable analysis in resected tumours with CTx (each p < 0.05). In biopsies before CTx, CIN-high predicted tumour regression (p = 0.026), but was not prognostically relevant. CONCLUSION: A refined CIN classification reveals tumours with different biological characteristics and potential clinical implications.

Comprehensive Immunohistochemical Study of the SWI/SNF Complex Expression Status in Gastric Cancer Reveals an Adverse Prognosis of SWI/SNF Deficiency in Genomically Stable Gastric Carcinomas.

The SWI/SNF complex has important functions in the mobilization of nucleosomes and consequently influences gene expression. Numerous studies have demonstrated that mutations or deficiency of one or more subunits can have an oncogenic effect and influence the development, progression, and eventual therapy resistance of tumor diseases. Genes encoding subunits of the SWI/SNF complex are mutated in approximately 20% of all human tumors. This study aimed to investigate the frequency, association with clinicopathological characteristics, and prognosis of immunohistochemical expression of proteins of the SWI/SNF complexes, SMARCA2, SMARCA4 SMARCB1, ARID1A, ARID1B, and PBRM1 in 477 adenocarcinomas of the stomach and gastroesophageal junction. Additionally, the tumors were classified immunohistochemically in analogy to The Cancer Genome Atlas (TCGA) classification. Overall, 32% of cases demonstrated aberrant expression of the SWI/SNF complex. Complete loss of SMARCA4 was detected in three cases (0.6%) and was associated with adverse clinical characteristics. SWI/SNF aberration emerged as an independent negative prognostic factor for overall survival in genomically stable patients in analogy to TCGA. In conclusion, determination of SWI/SNF status could be suggested in routine diagnostics in genomically stable tumors to identify patients who might benefit from new therapeutic options.

Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study.

BACKGROUND: Response to immunotherapy in gastric cancer is associated with microsatellite instability (or mismatch repair deficiency) and Epstein-Barr virus (EBV) positivity. We therefore aimed to develop and validate deep learning-based classifiers to detect microsatellite instability and EBV status from routine histology slides. METHODS: In this retrospective, multicentre study, we collected tissue samples from ten cohorts of patients with gastric cancer from seven countries (South Korea, Switzerland, Japan, Italy, Germany, the UK and the USA). We trained a deep learning-based classifier to detect microsatellite instability and EBV positivity from digitised, haematoxylin and eosin stained resection slides without annotating tumour containing regions. The performance of the classifier was assessed by within-cohort cross-validation in all ten cohorts and by external validation, for which we split the cohorts into a five-cohort training dataset and a five-cohort test dataset. We measured the area under the receiver operating curve (AUROC) for detection of microsatellite instability and EBV status. Microsatellite instability and EBV status were determined to be detectable if the lower bound of the 95% CI for the AUROC was above 0·5. FINDINGS: Across the ten cohorts, our analysis included 2823 patients with known microsatellite instability status and 2685 patients with known EBV status. In the within-cohort cross-validation, the deep learning-based classifier could detect microsatellite instability status in nine of ten cohorts, with AUROCs ranging from 0·597 (95% CI 0·522-0·737) to 0·836 (0·795-0·880) and EBV status in five of eight cohorts, with AUROCs ranging from 0·819 (0·752-0·841) to 0·897 (0·513-0·966). Training a classifier on the pooled training dataset and testing it on the five remaining cohorts resulted in high classification performance with AUROCs ranging from 0·723 (95% CI 0·676-0·794) to 0·863 (0·747-0·969) for detection of microsatellite instability and from 0·672 (0·403-0·989) to 0·859 (0·823-0·919) for detection of EBV status. INTERPRETATION: Classifiers became increasingly robust when trained on pooled cohorts. After prospective validation, this deep learning-based tissue classification system could be used as an inexpensive predictive biomarker for immunotherapy in gastric cancer. FUNDING: German Cancer Aid and German Federal Ministry of Health.