COVID-19. Biology, pathophysiology, and immunology: a pathologist view.

Even if the SARS-CoV-2 pandemic has been declared over, several risks and clinical problems remain to be faced, including long-COVID sequelae and possible outbreaks of pathogenic variants. Intense research on COVID-19 has provided in these few years a striking amount of data covering different fields and disciplines, which can help to provide a knowledge shield against new potential infective spreads, and may also potentially be applied to other fields of medicine, including oncology and neurology. Nevertheless, areas of uncertainty still remain regarding the pathogenic mechanisms that subtend the multifaceted manifestations of the disease. To better clarify the pathogenesis of the disease, a systematic multidisciplinary evaluation of the many mechanisms involved in COVID-19 is mandatory, including clinical, physiological, radiological, immunological and pathological studies. In COVID-19 syndrome the pathological studies have been mainly performed on autopsy cases, and only a few studies are available on biopsies. Nevertheless, these studies have provided relevant information that can substantially contribute to decipher the complex scenario characterizing the different forms of COVID-19 and long-COVID-19. In this review the data provided by pathological investigations are recapitulated and discussed, in the light of different hypothesis and data provided by clinical, physiological and immunological data.

mTOR eosinophilic renal cell carcinoma: a distinctive tumor characterized by mTOR mutation, loss of chromosome 1, cathepsin-K expression, and response to target therapy.

In the spectrum of oncocytic renal neoplasms, a subset of tumors with high-grade-appearing histologic features harboring pathogenic mutations in mammalian target of rapamycin (mTOR) and hitherto clinical indolent behavior has been described. Three cases (2F,1 M) with histologically documented metastases (lymph node, skull, and liver) were retrieved and extensively investigated by immunohistochemistry, FISH, and next-generation sequencing. Tumors were composed of eosinophilic cells with prominent nucleoli (G3 by ISUP/WHO) arranged in solid to nested architecture. Additionally, there were larger cells with perinuclear cytoplasmic shrinkage and sparse basophilic Nissl-like granules, superficially resembling the so-called spider cells of cardiac rhabdomyomas. The renal tumors, including the skull and liver metastases, showed immunoexpression PAX8, CK8-18, and cathepsin-K, and negativity for vimentin. NGS identified mTOR genetic alterations in the three cases, including the skull and liver metastases. One patient was then treated with Everolimus (mTOR inhibitors) with clinical response (metastatic tumor shrinkage). We present a distinct renal tumor characterized by high-grade eosinophilic cells, cathepsin-K immunohistochemical expression, and harboring mTOR gene mutations demonstrating a malignant potential and showing responsiveness to mTOR inhibitors.

STING is a prognostic factor related to tumor necrosis, sarcomatoid dedifferentiation, and distant metastasis in clear cell renal cell carcinoma.

STING is a molecule involved in immune reactions against double-stranded DNA fragments, released in infective and neoplastic diseases, whose role in the interactions between immune and neoplastic cells in clear cell renal cell carcinoma has not been studied yet. We investigated the immunohistochemical expression of STING in a series of 146 clear-cell renal cell carcinomas and correlated it with the main pathological prognostic factors. Furthermore, tumoral inflammatory infiltrate was evaluated and studied for the subpopulations of lymphocytes. Expression of STING was observed in 36% (53/146) of the samples, more frequently in high-grade (G3-G4) tumors (48%,43/90) and recurrent/metastatic ones (75%, 24/32) than in low grade (G1-G2) and indolent neoplasms (16%, 9/55). STING staining correlated with parameters of aggressive behavior, including coagulative granular necrosis (p = 0.001), stage (p < 0.001), and development of metastases (p < 0.001). Among prognostic parameters, STING immune expression reached an independent statistical significance (p = 0.029) in multivariable analysis, along with the stage and the presence of coagulative granular necrosis. About tumor immune-environment, no significant statistical association has been demonstrated between tumor-infiltrating lymphocytes and STING. Our results provide novel insights regarding the role of STING in aggressive clear cell renal cell carcinomas, suggesting its adoption as a prognostic marker and a potentially targetable molecule for specific immunotherapies.

Well-differentiated neuroendocrine tumor of the urinary bladder expressing GATA 3.

Neuroendocrine neoplasms of the urinary bladder are uncommon tumors represented by small-cell neuroendocrine carcinoma and by fewer cases of large-cell neuroendocrine carcinomas and well-differentiated neuroendocrine tumors. Less than 30 examples of this latter entity have been published so far and consisted of clinically indolent lesions mainly located in the bladder neck arranged in a pseudo-glandular architecture often associated with reactive urothelial changes like cystitis cystica/glandularis. Due to their infrequency, pathologists may face difficulty to recognize this proliferation considering it as part of cystitis cystica/glandularis or misinterpreting it as nested urothelial carcinoma, paraganglioma, or secondary bladder involvement by prostatic adenocarcinoma. Herein the case of a 51-year-old female diagnosed with a well-differentiated neuroendocrine tumor of the bladder immunohistochemically expressing GATA3 is reported, pointing out either the pitfall in the differential diagnosis with cystitis cystica/glandularis, nested urothelial carcinoma, and paraganglioma or its usefulness in the differential diagnosis with prostatic adenocarcinoma.

Bcl-10, trypsin and synaptophysin helps recognize acinar cell and mixed acinar neuroendocrine cell carcinoma of the pancreas on both preoperative cytological samples and needle biopsy specimens.

OBJECTIVE: Acinar cell carcinoma (ACC) of the pancreas are known to be rare and difficult to be recognize because they mimic other unrelated tumors (neuroendocrine, solid pseudopapillary) with different clinical behavior. Especially in the setting of inoperable patients, fine needle aspiration cytology (FNAC), core needle biopsy (FNAB) and immunocyto/histochemistry (ICC/IHC) play a crucial role in the differential diagnosis. The biological material available for ICC tests obtained by minimal invasive procedures is usually limited. Aim of the current study was to evaluate diagnostic panel based on a limited number of ICC markers for typing preoperatively ACC of the pancreas. METHODS: Of 1820 needle sampling procedures performed and related to pancreatic lesions, 21 cases were extracted with a confirmed diagnosis of ACC on histology. Of them,12 were pure ACC and 9 mixed acinar-neuroendocrine carcinoma (MANEC). Smears of ACC, MANEC and a control group composed of 34neuroendocrine, 7solid pseudopapillary, 50ductal and 4 adenosquamous carcinoma were assessed with an ICC panel made up of BCL10, trypsin, synaptophysin, chromograninA, ß-catenin. RESULTS: On cytology, BCL10 sensitivity and specificity for ACC was 100%. Trypsin correctly recognized 90% of the cases. Synaptophysin was helpful to correctly identify all the cases with a mixed neuroendocrine component. No significant cross-reaction was observed between BCL10 and trypsin in any of the control group case. CONCLUSIONS: BCL10 is a determinant marker for the diagnosis of acinar cell carcinoma and mixed acinar neuroendocrine cell carcinoma of the pancreas in a pre-operative citologic/histologic setting.

Metabolomics of Prostate Cancer Gleason Score in Tumor Tissue and Serum.

Gleason score, a measure of prostate tumor differentiation, is the strongest predictor of lethal prostate cancer at the time of diagnosis. Metabolomic profiling of tumor and of patient serum could identify biomarkers of aggressive disease and lead to the development of a less-invasive assay to perform active surveillance monitoring. Metabolomic profiling of prostate tissue and serum samples was performed. Metabolite levels and metabolite sets were compared across Gleason scores. Machine learning algorithms were trained and tuned to predict transformation or differentiation status from metabolite data. A total of 135 metabolites were significantly different (P adjusted < 0.05) in tumor versus normal tissue, and pathway analysis identified one sugar metabolism pathway (P adjusted = 0.03). Machine learning identified profiles that predicted tumor versus normal tissue (AUC of 0.82 ± 0.08). In tumor tissue, 25 metabolites were associated with Gleason score (unadjusted P < 0.05), 4 increased in high grade while the remainder were enriched in low grade. While pyroglutamine and 1,5-anhydroglucitol were correlated (0.73 and 0.72, respectively) between tissue and serum from the same patient, no metabolites were consistently associated with Gleason score in serum. Previously reported as well as novel metabolites with differing abundance were identified across tumor tissue. However, a "metabolite signature" for Gleason score was not obtained. This may be due to study design and analytic challenges that future studies should consider. IMPLICATIONS: Metabolic profiling can distinguish benign and neoplastic tissues. A novel unsupervised machine learning method can be utilized to achieve this distinction.

The Landscape of Digital Pathology in Transplantation: From the Beginning to the Virtual E-Slide.

BACKGROUND: Digital pathology has progressed over the last two decades, with many clinical and nonclinical applications. Transplantation pathology is a highly specialized field in which the majority of practicing pathologists do not have sufficient expertise to handle critical needs. In this context, digital pathology has proven to be useful as it allows for timely access to expert second-opinion teleconsultation. The aim of this study was to review the experience of the application of digital pathology to the field of transplantation. METHODS: Papers on this topic were retrieved using PubMed as a search engine. Inclusion criteria were the presence of transplantation setting and the use of any type of digital image with or without the use of image analysis tools; the search was restricted to English language papers published in the 25 years until December 31, 2018. RESULTS: Literature regarding digital transplant pathology is mostly about the digital interpretation of posttransplant biopsies (75 vs. 19), with 15/75 (20%) articles focusing on agreement/reproducibility. Several papers concentrated on the correlation between biopsy features assessed by digital image analysis (DIA) and clinical outcome (45/75, 60%). Whole-slide imaging (WSI) only appeared in recent publications, starting from 2011 (13/75, 17.3%). Papers dealing with preimplantation biopsy are less numerous, the majority (13/19, 68.4%) of which focus on diagnostic agreement between digital microscopy and light microscopy (LM), with WSI technology being used in only a small quota of papers (4/19, 21.1%). CONCLUSIONS: Overall, published studies show good concordance between digital microscopy and LM modalities for diagnosis. DIA has the potential to increase diagnostic reproducibility and facilitate the identification and quantification of histological parameters. Thus, with advancing technology such as faster scanning times, better image resolution, and novel image algorithms, it is likely that WSI will eventually replace LM.