The Banff community summoned the TMA Banff Working Group to develop minimum diagnostic criteria (MDC) and recommendations for renal transplant TMA (Tx-TMA) diagnosis, which currently lacks standardized criteria. Using the Delphi method for consensus generation, 23 nephropathologists (panelists) with >3 years of diagnostic experience with Tx-TMA were asked to list light, immunofluorescence, and electron microscopic, clinical and laboratory criteria and differential diagnoses for Tx-TMA. Delphi was modified to include 2 validations rounds with histological evaluation of whole slide images of 37 transplant biopsies (28 TMA and 9 non-TMA). Starting with 338 criteria in R1, MDC were narrowed down to 24 in R8 generating 18 pathological, 2 clinical, 4 laboratory criteria, and 8 differential diagnoses. The panelists reached a good level of agreement (70%) on 76% of the validated cases. For the first time in Banff classification, Delphi was used to reach consensus on MDC for Tx-TMA. Phase I of the study (pathology phase) will be used as a model for Phase II (nephrology phase) for consensus regarding clinical and laboratory criteria. Eventually in Phase III (consensus of the consensus groups) and the final MDC for Tx-TMA will be reported to the transplantation community.

The Thrombotic Microangiopathy Banff Working Group (TMA-BWG) was formed in 2015 to survey current practices and develop minimum diagnostic criteria (MDC) for renal transplant TMA (Tx-TMA). To generate consensus among pathologists and nephrologists, the TMA BWG designed a 3-Phase study. Phase I of the study is presented here. Using the Delphi methodology, 23 panelists with >3 years of diagnostic experience with Tx-TMA pathology listed their MDC suggesting light, immunofluorescence, and electron microscopy lesions, clinical and laboratory information, and differential diagnoses. Nine rounds (R) of consensus resulted in MDC validated during two Rs using online evaluation of whole slide digital images of 37 biopsies (28 TMA, 9 non-TMA). Starting with 338 criteria the process resulted in 24 criteria and 8 differential diagnoses including 18 pathologic, 2 clinical, and 4 laboratory criteria. Results show that 3/4 of the panelists agreed on the diagnosis of 3/4 of cases. The process also allowed definition refinement for 4 light and 4 electron microscopy lesions. For the first time in Banff classification, the Delphi methodology was used to generate consensus. The study shows that Delphi is a democratic and cost-effective method allowing rapid consensus generation among numerous physicians dealing with large number of criteria in transplantation.

BACKGROUND: Obesity is an established risk factor for colorectal cancer (CRC), but the evidence for the association is inconsistent across molecular subtypes of the disease. METHODS: We pooled data on body mass index (BMI), tumor microsatellite instability status, CpG island methylator phenotype status, BRAF and KRAS mutations, and Jass classification types for 11 872 CRC cases and 11 013 controls from 11 observational studies. We used multinomial logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusted for covariables. RESULTS: Higher BMI was associated with increased CRC risk (OR per 5 kg/m2 = 1.18, 95% CI = 1.15 to 1.22). The positive association was stronger for men than women but similar across tumor subtypes defined by individual molecular markers. In analyses by Jass type, higher BMI was associated with elevated CRC risk for types 1-4 cases but not for type 5 CRC cases (considered familial-like/Lynch syndrome microsatellite instability-H, CpG island methylator phenotype-low or negative, BRAF-wild type, KRAS-wild type, OR = 1.04, 95% CI = 0.90 to 1.20). This pattern of associations for BMI and Jass types was consistent by sex and design of contributing studies (cohort or case-control). CONCLUSIONS: In contrast to previous reports with fewer study participants, we found limited evidence of heterogeneity for the association between BMI and CRC risk according to molecular subtype, suggesting that obesity influences nearly all major pathways involved in colorectal carcinogenesis. The null association observed for the Jass type 5 suggests that BMI is not a risk factor for the development of CRC for individuals with Lynch syndrome.

Background. Liver allografts protect renal allografts from the same donor from some, but not all, preformed donor specific alloantibodies (DSA). However, the precise mechanisms of protection and the potential for more subtle alterations/injuries within the grafts resulting from DSA interactions require further study. Methods. We reevaluated allograft biopsies from simultaneous liver-kidney transplant recipients who had both allografts biopsied within 60 d of one another and within 30 d of DSA being positive in serum (positive: mean florescence intensity ≥5000). Routine histology, C4d staining, and specialized immunohistochemistry for Kupffer cells (KCs; CD163) and a C4d receptor immunoglobulin-like transcript-4 were carried out in 4 patients with 6 paired biopsies. Results. Overt antibody-mediated rejection was found in 3 of 4 renal and liver allografts. One patient had biopsy-confirmed renal and liver allograft antibody-mediated rejection despite serum clearance of DSA. All biopsies showed KC hypertrophy (minimal: 1; mild: 2; moderate: 1; severe: 2) and cytoplasmic C4d KC staining was easily detected in 2 biopsies from 2 patients; minimal and negative in 2 biopsies each. Implications of which are discussed. Control 1-y protocol liver allograft biopsies from DSA- recipients showed neither KC hypertrophy nor KC C4d staining (n = 6). Conclusions. Partial renal allograft protection by a liver allograft from the same donor may be partially mediated by phagocytosis/elimination of antibody and complement split products by KCs, as shown decades ago in controlled sensitized experimental animal experiments.

This study aimed to enhance antitumor immune responses to pancreatic cancer via Ab-based blockade of IL-6 and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4). Mice bearing s.c. or orthotopic pancreatic tumors were treated with blocking Abs to IL‑6 and/or CTLA-4. In both tumor models, dual IL-6 and CTLA-4 blockade significantly inhibited tumor growth. Additional investigations revealed that dual therapy induced an overwhelming infiltration of T cells into the tumor as well as changes in CD4+ T cell subsets. Dual blockade therapy elicited CD4+ T cells to secrete increased IFN-γ in vitro. Likewise, in vitro stimulation of pancreatic tumor cells with IFN-γ profoundly increased tumor cell production of CXCR3-specific chemokines, even in the presence of IL-6. In vivo blockade of CXCR3 prevented orthotopic tumor regression in the presence of the combination treatment, demonstrating a dependence on the CXCR3 axis for antitumor efficacy. Both CD4+ and CD8+ T cells were required for the antitumor activity of this combination therapy, as their in vivo depletion via Abs impaired outcomes. These data represent the first report to our knowledge of IL-6 and CTLA‑4 blockade as a means to regress pancreatic tumors with defined operative mechanisms of efficacy.

Costimulation blockade with the B7-CD28 pathway-specific agent belatacept is now used in clinical kidney transplantation, but its efficacy remains imperfect. Numerous alternate costimulatory pathways have been proposed as targets to synergize with belatacept, one of which being the inducible costimulator (ICOS)-ICOS ligand (ICOS-L) pathway. Combined ICOS-ICOS-L and CD28-B7 blockade has been shown to prevent rejection in mice, but has not been studied in primates. We therefore tested a novel ICOS-Ig human Fc-fusion protein in a nonhuman primate (NHP) kidney transplant model alone and in combination with belatacept. ICOS-Ig did not prolong rejection-free survival as a monotherapy or in combination with belatacept. In ICOS-Ig alone treated animals, most graft-infiltrating CD4+ and CD8+ T cells expressed ICOS, and ICOS+ T cells were present in peripheral blood to a lesser degree. Adding belatacept reduced the proportion of graft-infiltrating ICOS+ T cells and virtually eliminated their presence in peripheral blood. Graft-infiltrating T cells in belatacept-resistant rejection were primarily CD8+CD28-, but importantly, very few CD8+CD28- T cells expressed ICOS. We conclude that ICOS-Ig, alone or combined with belatacept, does not prolong renal allograft survival in NHPs. This may relate to selective loss of ICOS with CD28 loss. This study demonstrates that blockade of the ICOS-ICOS-Ligand pathway, when used as monotherapy or paired with CD28-B7 blockade, does not prolong renal allograft survival in a nonhuman primate kidney transplant model.

Among sensitized patients awaiting a transplant, females are disproportionately represented, partly because of pregnancy-induced sensitization. Using female NHPs sensitized by pregnancy alone, we examined the efficacy of costimulation blockade and proteasome inhibition for desensitization. Three animals received no desensitization (control), and seven animals received weekly carfilzomib (27 mg/m2) and belatacept (20 mg/kg) before kidney transplantation. All animals received renal allografts from crossmatch-positive/maximally MHC-mismatched donors. Controls and three desensitized animals received tacrolimus-based immunosuppression. Four desensitized animals received additional belatacept with tacrolimus-based immunosuppression. Multiparous females had less circulating donor-specific antibody when compared to skin-sensitized males before transplantation. While females receiving desensitization showed only a marginal survival benefit over control females (MST = 11 days versus 63 days), additional belatacept to posttransplant maintenance significantly prolonged graft survival (MST > 164 days) and suppressed posttransplant DSA and circulating follicular helper T-like cells. This combination of therapies demonstrates great potential to reduce antibody-mediated rejection in sensitized recipients.

OBJECTIVE: Lupus nephritis (LN) is diagnosed by biopsy, but longitudinal monitoring assessment methods are needed. Here, in this preliminary and hypothesis-generating study, we evaluate the potential for using urine proteomics as a non-invasive method to monitor disease activity and damage. Urinary biomarkers were identified and used to develop two novel algorithms that were used to predict LN activity and chronicity. METHODS: Baseline urine samples were collected for four cohorts (healthy donors (HDs, n=18), LN (n=42), SLE (n=17) or non-LN kidney disease biopsy control (n=9)), and over 1 year for patients with LN (n=42). Baseline kidney biopsies were available for the LN (n=46) and biopsy control groups (n=9). High-throughput proteomics platforms were used to identify urinary analytes ≥1.5 SD from HD means, which were subjected to stepwise, univariate and multivariate logistic regression modelling to develop predictive algorithms for National Institutes of Health Activity Index (NIH-AI)/National Institutes of Health Chronicity Index (NIH-CI) scores. Kidney biopsies were analysed for macrophage and neutrophil markers using immunohistochemistry (IHC). RESULTS: In total, 112 urine analytes were identified from LN, SLE and biopsy control patients as both quantifiable and overexpressed compared with HDs. Regression analysis identified proteins associated with the NIH-AI (n=30) and NIH-CI (n=26), with four analytes common to both groups, demonstrating a difference in the mechanisms associated with NIH-AI and NIH-CI. Pathway analysis of the NIH-AI and NIH-CI analytes identified granulocyte-associated and macrophage-associated pathways, and the presence of these cells was confirmed by IHC in kidney biopsies. Four markers each for the NIH-AI and NIH-CI were identified and used in the predictive algorithms. The NIH-AI algorithm sensitivity and specificity were both 93% with a false-positive rate (FPR) of 7%. The NIH-CI algorithm sensitivity was 88%, specificity 96% and FPR 4%. The accuracy for both models was 93%. CONCLUSIONS: Longitudinal predictions suggested that patients with baseline NIH-AI scores of ≥8 were most sensitive to improvement over 6-12 months. Viable approaches such as this may enable the use of urine samples to monitor LN over time.

Background: Artificial intelligence (AI) is rapidly fuelling a fundamental transformation in the practice of pathology. However, clinical integration remains challenging, with no AI algorithms to date in routine adoption within typical anatomic pathology (AP) laboratories. This survey gathered current expert perspectives and expectations regarding the role of AI in AP from those with first-hand computational pathology and AI experience. Methods: Perspectives were solicited using the Delphi method from 24 subject matter experts between December 2020 and February 2021 regarding the anticipated role of AI in pathology by the year 2030. The study consisted of three consecutive rounds: 1) an open-ended, free response questionnaire generating a list of survey items; 2) a Likert-scale survey scored by experts and analysed for consensus; and 3) a repeat survey of items not reaching consensus to obtain further expert consensus. Findings: Consensus opinions were reached on 141 of 180 survey items (78.3%). Experts agreed that AI would be routinely and impactfully used within AP laboratory and pathologist clinical workflows by 2030. High consensus was reached on 100 items across nine categories encompassing the impact of AI on (1) pathology key performance indicators (KPIs) and (2) the pathology workforce and specific tasks performed by (3) pathologists and (4) AP lab technicians, as well as (5) specific AI applications and their likelihood of routine use by 2030, (6) AI's role in integrated diagnostics, (7) pathology tasks likely to be fully automated using AI, and (8) regulatory/legal and (9) ethical aspects of AI integration in pathology. Interpretation: This systematic consensus study details the expected short-to-mid-term impact of AI on pathology practice. These findings provide timely and relevant information regarding future care delivery in pathology and raise key practical, ethical, and legal challenges that must be addressed prior to AI's successful clinical implementation. Funding: No specific funding was provided for this study.

Inconsistencies in the preparation of histology slides and whole-slide images (WSIs) may lead to challenges with subsequent image analysis and machine learning approaches for interrogating the WSI. These variabilities are especially pronounced in multicenter cohorts, where batch effects (i.e. systematic technical artifacts unrelated to biological variability) may introduce biases to machine learning algorithms. To date, manual quality control (QC) has been the de facto standard for dataset curation, but remains highly subjective and is too laborious in light of the increasing scale of tissue slide digitization efforts. This study aimed to evaluate a computer-aided QC pipeline for facilitating a reproducible QC process of WSI datasets. An open source tool, HistoQC, was employed to identify image artifacts and compute quantitative metrics describing visual attributes of WSIs to the Nephrotic Syndrome Study Network (NEPTUNE) digital pathology repository. A comparison in inter-reader concordance between HistoQC aided and unaided curation was performed to quantify improvements in curation reproducibility. HistoQC metrics were additionally employed to quantify the presence of batch effects within NEPTUNE WSIs. Of the 1814 WSIs (458 H&E, 470 PAS, 438 silver, 448 trichrome) from n = 512 cases considered in this study, approximately 9% (163) were identified as unsuitable for subsequent computational analysis. The concordance in the identification of these WSIs among computational pathologists rose from moderate (Gwet's AC1 range 0.43 to 0.59 across stains) to excellent (Gwet's AC1 range 0.79 to 0.93 across stains) agreement when aided by HistoQC. Furthermore, statistically significant batch effects (p < 0.001) in the NEPTUNE WSI dataset were discovered. Taken together, our findings strongly suggest that quantitative QC is a necessary step in the curation of digital pathology cohorts. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.