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Introduction: Colorectal cancers (CRCs) deficient in the DNA mismatch repair protein MutL homolog 1 (MLH1) display distinct clinicopathological features and require a different therapeutic approach compared to CRCs with MLH1 proficiency. However, the molecular basis of this fundamental difference remains elusive. Here, we report that MLH1-deficient CRCs exhibit reduced levels of the cytoskeletal scaffolding protein non-erythroid spectrin αII (SPTAN1), and that tumor progression and metastasis of CRCs correlate with SPTAN1 levels.
Methods and results: To investigate the link between MLH1 and SPTAN1 in cancer progression, a cohort of 189 patients with CRC was analyzed by immunohistochemistry. Compared with the surrounding normal mucosa, SPTAN1 expression was reduced in MLH1-deficient CRCs, whereas MLH1-proficient CRCs showed a significant upregulation of SPTAN1. Overall, we identified a strong correlation between MLH1 status and SPTAN1 expression. When comparing TNM classification and SPTAN1 levels, we found higher SPTAN1 levels in stage I CRCs, while stages II to IV showed a gradual reduction of SPTAN1 expression. In addition, SPTAN1 expression was lower in metastatic compared with non-metastatic CRCs. Knockdown of SPTAN1 in CRC cell lines demonstrated decreased cell viability, impaired cellular mobility and reduced cell-cell contact formation, indicating that SPTAN1 plays an important role in cell growth and cell attachment. The observed weakened cell-cell contact of SPTAN1 knockdown cells might indicate that tumor cells expressing low levels of SPTAN1 detach from their primary tumor and metastasize more easily.
Conclusion: Taken together, we demonstrate that MLH1 deficiency, low SPTAN1 expression, and tumor progression and metastasis are in close relation. We conclude that SPTAN1 is a candidate molecule explaining the tumor progression and metastasis of MLH1-deficient CRCs. The detailed analysis of SPTAN1 is now mandatory to substantiate its relevance and its potential value as a candidate protein for targeted therapy, and as a predictive marker of cancer aggressiveness.
The Gleason grading system remains the most powerful prognostic predictor for patients with prostate cancer since the 1960s. Its application requires highly-trained pathologists, is tedious and yet suffers from limited inter-pathologist reproducibility, especially for the intermediate Gleason score 7. Automated annotation procedures constitute a viable solution to remedy these limitations. In this study, we present a deep learning approach for automated Gleason grading of prostate cancer tissue microarrays with Hematoxylin and Eosin (H&E) staining. Our system was trained using detailed Gleason annotations on a discovery cohort of 641 patients and was then evaluated on an independent test cohort of 245 patients annotated by two pathologists. On the test cohort, the inter-annotator agreements between the model and each pathologist, quantified via Cohen’s quadratic kappa statistic, were 0.75 and 0.71 respectively, comparable with the inter-pathologist agreement (kappa = 0.71). Furthermore, the model’s Gleason score assignments achieved pathology expert-level stratification of patients into prognostically distinct groups, on the basis of disease-specific survival data available for the test cohort. Overall, our study shows promising results regarding the applicability of deep learning-based solutions towards more objective and reproducible prostate cancer grading, especially for cases with heterogeneous Gleason patterns.
Objective: We aimed to assess the correlation between serum prostate-specific antigen (PSA) and tumor burden in prostate cancer (PCa) patients undergoing radical prostatectomy (RP), because estimation of tumor burden is of high value, e.g., in men undergoing RP or with biochemical recurrence after RP. Patients and Methods: From January 2019 to June 2020, 179 consecutive PCa patients after RP with information on tumor and prostate weight were retrospectively identified from our prospective institutional RP database. Patients with preoperative systemic therapy (n=19), metastases (cM1, n=5), and locally progressed PCa (pT4 or pN1, n=50) were excluded from analyses. Histopathological features, including total weight of the prostate and specific tumor weight, were recorded by specialized uro-pathologists. Linear regression models were performed to evaluate the effect of PSA on tumor burden, measured by tumor weight after adjustment for patient and tumor characteristics. Results: Overall, median preoperative PSA was 7.0 ng/ml (interquartile range [IQR]: 5.41–10) and median age at surgery was 66 years (IQR: 61-71). Median prostate weight was 34 g (IQR: 26–46) and median tumor weight was 3.7 g (IQR: 1.8–7.1), respectively. In multivariable linear regression analysis after adjustment for patients and tumor characteristics, a significant, positive correlation could be detected between preoperative PSA and tumor weight (coefficient [coef.]: 0.37, CI: 0.15–0.6, p=0.001), indicating a robust increase in PSA of almost 0.4 ng/ml per 1g tumor weight. Conclusion: Preoperative PSA was significantly correlated with tumor weight in PCa patients undergoing RP, with an increase in PSA of almost 0.4 ng/ml per 1 g tumor weight. This might help to estimate both tumor burden before undergoing RP and in case of biochemical recurrence.
Background: To test the value of immunohistochemistry (IHC) staining in prostate biopsies for changes in biopsy results and its impact on treatment decision-making. Methods: Between January 2017–June 2020, all patients undergoing prostate biopsies were identified and evaluated regarding additional IHC staining for diagnostic purpose. Final pathologic results after radical prostatectomy (RP) were analyzed regarding the effect of IHC at biopsy. Results: Of 606 biopsies, 350 (58.7%) received additional IHC staining. Of those, prostate cancer (PCa) was found in 208 patients (59.4%); while in 142 patients (40.6%), PCa could be ruled out through IHC. IHC patients harbored significantly more often Gleason 6 in biopsy (p < 0.01) and less suspicious baseline characteristics than patients without IHC. Of 185 patients with positive IHC and PCa detection, IHC led to a change in biopsy results in 81 (43.8%) patients. Of these patients with changes in biopsy results due to IHC, 42 (51.9%) underwent RP with 59.5% harboring ≥pT3 and/or Gleason 7–10. Conclusions: Patients with IHC stains had less suspicious characteristics than patients without IHC. Moreover, in patients with positive IHC and PCa detection, a change in biopsy results was observed in >40%. Patients with changes in biopsy results partly underwent RP, in which 60% harbored significant PCa.
Introduction: Penile carcinomas are rare tumors throughout Europe. Therefore, little attention is drawn to this disease. That makes it important to study tumor-associated key metrics and relate these to known data on penile neoplasias. Materials and methods: A cohort of 60 well-defined penile invasive carcinomas with known human papillomavirus (HPV) infection status was investigated. Data on tumor type, grading and staging were recorded. Additionally, data on the peri- and intratumoral immune cell infiltrate in a semiquanititave manner applying an HE stain were assessed. Results: Our study showed a significant correlation of immune cell infiltrate and pT stage with overall survival. Therefore, in a subset of tumors, PD-L1 staining was applied. For tumor proportion score (TPS), 26 of 30 samples (87%) were scored >0%. For the immune cell score (IC), 28 of 30 samples (93%) were defined as >0% and for CPS, 29 of 30 samples (97%) scored >0. PD-L1 expression was not associated with overall survival. Conclusion: PD-L1 is expressed in penile carcinomas, providing a rationale for targeted therapy with checkpoint inhibitors. We were able to show that immune reaction appears to be prognostically relevant. These data enhance the need for further studies on the immune cell infiltrate in penile neoplasias and show that PD-L1 expression is existent in our cohort, which may be a potential target for checkpoint inhibitor therapy.
Oncogenic rearrangements leading to targetable gene fusions are well-established cancer driver events in lung adenocarcinoma. Accurate and reliable detection of these gene fusions is crucial to select the appropriate targeted therapy for each patient. We compared the targeted next-generation-sequencing Oncomine Focus Assay (OFA; Thermo Fisher Scientific) with conventional ALK FISH and anti-Alk immunohistochemistry in a cohort of 52 lung adenocarcinomas (10 ALK rearranged, 18 non-ALK rearranged, and 24 untested cases). We found a sensitivity and specificity of 100% for detection of ALK rearrangements using the OFA panel. In addition, targeted next generation sequencing allowed us to analyze a set of 23 driver genes in a single assay. Besides EML4-ALK (11/52 cases), we detected EZR-ROS1 (1/52 cases), KIF5B-RET (1/52 cases) and MET-MET (4/52 cases) fusions. All EML4-ALK, EZR-ROS1 and KIF5B-RET fusions were confirmed by multiplexed targeted next generation sequencing assay (Oncomine Solid Tumor Fusion Transcript Kit, Thermo Fisher Scientific). All cases with EML4-ALK rearrangement were confirmed by Alk immunohistochemistry and all but one by ALK FISH. In our experience, targeted next-generation sequencing is a reliable and timesaving tool for multiplexed detection of targetable rearrangements. Therefore, targeted next-generation sequencing represents an efficient alternative to time-consuming single target assays currently used in molecular pathology.
Formalin‐fixed, paraffin‐embedded (FFPE ), biobanked tissue samples offer an invaluable resource for clinical and biomarker research. Here, we developed a pressure cycling technology (PCT )‐SWATH mass spectrometry workflow to analyze FFPE tissue proteomes and applied it to the stratification of prostate cancer (PC a) and diffuse large B‐cell lymphoma (DLBCL ) samples. We show that the proteome patterns of FFPE PC a tissue samples and their analogous fresh‐frozen (FF ) counterparts have a high degree of similarity and we confirmed multiple proteins consistently regulated in PC a tissues in an independent sample cohort. We further demonstrate temporal stability of proteome patterns from FFPE samples that were stored between 1 and 15 years in a biobank and show a high degree of the proteome pattern similarity between two types of histological regions in small FFPE samples, that is, punched tissue biopsies and thin tissue sections of micrometer thickness, despite the existence of a certain degree of biological variations. Applying the method to two independent DLBCL cohorts, we identified myeloperoxidase, a peroxidase enzyme, as a novel prognostic marker. In summary, this study presents a robust proteomic method to analyze bulk and biopsy FFPE tissues and reports the first systematic comparison of proteome maps generated from FFPE and FF samples. Our data demonstrate the practicality and superiority of FFPE over FF samples for proteome in biomarker discovery. Promising biomarker candidates for PC a and DLBCL have been discovered.