The role of B cells in antitumor immunity and their impact on emerging immunotherapies is increasingly gaining attention. B-cell effector functions include not only secretion of antibodies, but also presentation of antigens to T cells. A physiologic B-cell subset with immunostimulatory properties was described in humans, defined by a high expression of CD86 and downregulation of CD21. We used multicolor flow cytometry and IHC to elucidate abundance and spatial distribution of these antigen-presenting B cells (BAPC) in blood (peripheral blood mononuclear cells, PBMC) and tumor samples of 237 patients with cancer. Antigen-specific T-cell responses to cancer testis antigens were determined using tetramer staining and sorted BAPCs in FluoroSpot assays for selected patients. We found that BAPCs were increased in the tumor microenvironment of 9 of 10 analyzed cancer types with site-specific variation. BAPCs were not increased in renal cell carcinoma, whereas we found a systemic increase with elevated fractions in tumor-infiltrating lymphocytes (TIL) and PBMCs of patients with colorectal cancer and gastroesophageal adenocarcinoma. BAPCs were localized in lymphoid follicles of tertiary lymphoid structures (TLS) and were enriched in tumors with increased numbers of TLSs. BAPCs isolated from tumor-draining lymph nodes of patients with cancer showed increased percentages of tumor antigen–specific B cells and induced responses of autologous T cells in vitro. Our results highlight the relevance of BAPCs as professional antigen-presenting cells in tumor immunity and provide a mechanistic rationale for the observed correlation of B-cell abundance and response to immune checkpoint inhibition.

BACKGROUND & AIMS:Early detection of neoplastic lesions is essential in patients with long-standing ulcerative colitis but the best technique of colonoscopy still is controversial. METHODS:We performed a prospective multicenter study in patients with long-standing ulcerative colitis. Two colonoscopies were performed in each patient within 3 weeks to 3 months. In white-light (WL) colonoscopy, stepwise random biopsy specimens (4 biopsy specimens every 10 cm), segmental random biopsies (2 biopsy specimens in 5 segments), and targeted biopsy specimens were taken. In NBI colonoscopy, segmental and targeted biopsy specimens were taken. The sequence of WL and NBI colonoscopy was randomized. RESULTS:In 36 of 159 patients enrolled (22.6%), 54 lesions with intraepithelial neoplasia (IN) were found (51 low-grade, 3 high-grade). In WL colonoscopy we found 11 IN in stepwise biopsy specimens, 4 in segmental biopsy specimens, and 15 in targeted biopsy specimens. In NBI colonoscopy 7 IN were detected in segmental biopsy specimens and 24 IN were detected in targeted biopsy specimens. Almost all IN were found with one technique alone (k value of WL vs NBI, -0.86; P < .001). Statistically equivalent numbers of IN were found in NBI colonoscopywith targeted and segmental biopsy specimens as in WL colonoscopy with targeted and stepwise biopsy specimens, but with fewer biopsy specimens (11.9 vs 38.6 biopsy specimens, respectively; P < .001), and less withdrawal time was necessary (23 vs 13 min, respectively; P < .001). CONCLUSIONS:Stepwise biopsy specimens are indispensable in WL colonoscopy. The combination of targeted and segmental biopsy specimens in the NBI technique is as sensitive as targeted together with stepwise biopsy specimens in WL colonoscopy, but requires fewer biopsy specimens and less time. The highest sensitivity should be reached by combining the WL and NBI techniques by switching between the modes.

Purpose: Human papillomavirus (HPV) in oropharyngeal squamous cell carcinoma (OPSCC) is tumorigenic and has been associated with a favorable prognosis compared with OPSCC caused by tobacco, alcohol, and other carcinogens. Meanwhile, machine learning has evolved as a powerful tool to predict molecular and cellular alterations of medical images of various sources. Experimental Design: We generated a deep learning–based HPV prediction score (HPV-ps) on regular hematoxylin and eosin (H&E) stains and assessed its performance to predict HPV association using 273 patients from two different sites (OPSCC; Giessen, n = 163; Cologne, n = 110). Then, the prognostic relevance in a total of 594 patients (Giessen, Cologne, HNSCC TCGA) was evaluated. In addition, we investigated whether four board-certified pathologists could identify HPV association (n = 152) and compared the results to the classifier. Results: Although pathologists were able to diagnose HPV association from H&E-stained slides (AUC = 0.74, median of four observers), the interrater reliability was minimal (Light Kappa = 0.37; P = 0.129), as compared with AUC = 0.8 using the HPV-ps within two independent cohorts (n = 273). The HPV-ps identified individuals with a favorable prognosis in a total of 594 patients from three cohorts (Giessen, OPSCC, HR = 0.55, P &lt; 0.0001; Cologne, OPSCC, HR = 0.44, P = 0.0027; TCGA, non-OPSCC head and neck, HR = 0.69, P = 0.0073). Interestingly, the HPV-ps further stratified patients when combined with p16 status (Giessen, HR = 0.06, P &lt; 0.0001; Cologne, HR = 0.3, P = 0.046). Conclusions: Detection of HPV association in OPSCC using deep learning with help of regular H&E stains may either be used as a single biomarker, or in combination with p16 status, to identify patients with OPSCC with a favorable prognosis, potentially outperforming combined HPV-DNA/p16 status as a biomarker for patient stratification.

Vimentin is currently used to differentiate between malignant renal carcinomas and benign oncocytomas. Recent reports showing Vimentin positive oncocytomas seriously question the validity of this present diagnostic approach. Vimentin 3 is a spliced variant and ends with a unique C-terminal ending after exon 7 which differentiates it from the full length version that has 9 exons. Therefore, the protein size is different; the full length Vimentin version has a protein size of ~57 kDa and the truncated version of ~47 kDa. We designed an antibody, called Vim3, against the unique C-terminal ending of the Vimentin 3 variant. Using immune histology, immune fluorescence, Western blot, and qRT-PCR analysis, a Vim3 overexpression was detectable exclusively in oncocytoma, making the detection of Vim3 a potential specific marker for benign kidney tumors. This antibody is the first to clearly differentiate benign oncocytoma and the mimicking eosinophilic variants of the RCCs. This differentiation between malignant and benign RCCs is essential for operative planning, follow-up therapy, and patients' survival. In the future the usage of Vimentin antibodies in routine pathology has to be applied with care. Consideration must be given to Vimentin specific binding epitopes otherwise a misdiagnosis of the patients' tumor samples may result.

Background Molecular markers predicting survival in esophageal adenocarcinoma (EAC) are rare. Specifically, in favorable oncologic situations, e.g. nodal negativity or major neoadjuvant therapy response, there is a lack of additional risk factors that serve to predict patients’ outcome more precisely. This study evaluated X-linked inhibitor of apoptosis protein (XIAP) as a potential marker improving outcome prediction. Methods Tissue microarrays from 362 patients that were diagnosed with resectable EAC were included in the study. XIAP was stained by immunohistochemistry and correlated to clinical outcome, molecular markers and markers of the cellular tumor microenvironment. Results XIAP did not impact on overall survival (OS) in the whole study collective. Subgroup analyses stratifying for common genetic markers (TP53, ERBB2, ARID1A/SWI/SNF) did not disclose any impact of XIAP expression on survival. Detailed subgroup analyses of [1] nodal negative patients, [2] highly T-cell infiltrated tumors and [3] therapy responders to neoadjuvant treatment revealed a significant inverse role of high XIAP expression in these specific oncologic situations; elevated XIAP expression detrimentally affected patients’ outcome in these subgroups. [1]: OS XIAP low: 202 months (m) vs. XIAP high: 38 m; [2]: OS 116 m vs. 28.2 m; [3]: OS 31 m vs. 4 m). Conclusions Our data suggest XIAP expression in EAC as a worthy tool to improve outcome prediction in specific oncologic settings that might directly impact on clinical diagnosis and treatment of EAC in the future. Electronic supplementary material The online version of this article (10.1186/s12885-019-5722-1) contains supplementary material, which is available to authorized users.