Dasari, Surendra

ImportanceRosai-Dorfman disease (RDD) is a rare histiocytic neoplasm with recent studies showing alterations in the MAPK pathway, most commonly in the KRAS and MEK genes in about 40% of patients. Reports on the use of MEK-inhibitor therapy in RDD have been limited to small case studies. There are no approved treatments for this neoplasm, and therefore patients with RDD need efficacious treatments.ObjectiveTo study the outcomes after treatment with cobimetinib based on MAPK pathway alterations in patients with RDD.Design, Setting, and ParticipantsThis retrospective cohort study conducted at 2 tertiary care centers included patients with RDD who underwent treatment with cobimetinib between January 1, 2013, and December 1, 2021. Cobimetinib was administered at a dosage of 20 to 60 mg orally once daily as a single agent for 21 days in a 28-day cycle. Pathology was centrally reviewed. Response assessment was centrally conducted and was based on the established positron emission radiography response criteria used for clinical trials of targeted therapies in histiocytosis.Main Outcomes and MeasuresMain outcomes were overall response rate (ORR), progression-free survival (PFS), adverse events (AEs) of cobimetinib in the entire cohort, and ORRs and PFS based on MAPK pathway alterations in patients with RDD.ResultsA total of 16 patients (median [range] age at cobimetinib initiation, 57 [31-74] years; 11 [69%] women) were included in the study. The median follow-up duration was 19.0 months (95% CI, 8.4-27.8 months). The ORR was 63% (n = 10), including 5 complete responses and 5 partial responses. Somatic alterations in the KRAS or MEK genes were detected in 8 (50%) patients. Patients with KRAS or MEK alterations had significantly higher ORR (88% vs 38%; P = .03), deeper responses (complete responses among responders: 71% vs 0%; P = .002), and better PFS (at 1 year, 100% vs 29% were free from progression or death, respectively; P < .001) compared with those without such alterations. Grade 2 or higher AEs occurred in 12 (75%) patients, and 9 (56%) required dose reduction or temporary/permanent treatment discontinuation due to AEs.Conclusions and RelevanceIn this cohort study, treatment with cobimetinib was associated with positive outcomes in KRAS- or MEK-variant RDD. However, AEs requiring dose modifications were common.

Abstract Background: Altered hemodynamics in liver disease often results in overestimation of glomerular filtration rate (GFR) by creatinine-based GFR estimating (eGFR) equations. Recently, we have validated a novel eGFR equation based on serum myo-inositol, valine, and creatinine quantified by nuclear magnetic resonance spectroscopy in combination with cystatin C, age and sex (GFRNMR). We hypothesized that GFRNMRcould improve chronic kidney disease (CKD) classification in the setting of liver disease. Results: We conducted a retrospective multicenter study in 205 patients with chronic liver disease (CLD), comparing the performance of GFRNMRto that of validated CKD-EPI eGFR equations, including eGFRcr (based on creatinine) and eGFRcr-cys (based on both creatinine and cystatin C), using measured GFR as reference standard. GFRNMR outperformed all other equations with a low overall median bias (-1 vs. -6 to 4 ml/min/1.73 m2 for the other equations; p < 0.05) and the lowest difference in bias between reduced and preserved liver function (-3 vs. -16 to -8 ml/min/1.73 m2for other equations). Concordant classification by CKD stage was highest for GFRNMR (59% vs. 48% to 53%) and less biased in estimating CKD severity compared to the other equations. GFRNMR P30 accuracy (83%) was higher than that of eGFRcr (75%; p = 0.019) and comparable to that of eGFRcr-cys (86%; p = 0.578). Conclusions: Addition of myo-inositol and valine to creatinine and cystatin C in GFRNMR further improved GFR estimation in CLD patients and accurately stratified liver disease patients into CKD stages.

As part of the Multiple Myeloma Research Foundation (MMRF) immune atlas pilot project, we compared immune cells of multiple myeloma bone marrow samples from 18 patients assessed by single-cell RNA sequencing (scRNA-seq), mass cytometry (CyTOF), and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to understand the concordance of measurements among single-cell techniques. Cell type abundances are relatively consistent across the three approaches, while variations are observed in T cells, macrophages, and monocytes. Concordance and correlation analysis of cell type marker gene expression across different modalities highlighted the importance of choosing cell type marker genes best suited to particular modalities. By integrating data from these three assays, we found International Staging System stage 3 patients exhibited decreased CD4+ T/CD8+ T cells ratio. Moreover, we observed upregulation of RAC2 and PSMB9, in natural killer cells of fast progressors compared with those of nonprogressors, as revealed by both scRNA-seq and CITE-seq RNA measurement. This detailed examination of the immune microenvironment in multiple myeloma using multiple single-cell technologies revealed markers associated with multiple myeloma rapid progression which will be further characterized by the full-scale immune atlas project. Significance: scRNA-seq, CyTOF, and CITE-seq are increasingly used for evaluating cellular heterogeneity. Understanding their concordances is of great interest. To date, this study is the most comprehensive examination of the measurement of the immune microenvironment in multiple myeloma using the three techniques. Moreover, we identified markers predicted to be significantly associated with multiple myeloma rapid progression.

The spleen is a commonly encountered specimen in surgical pathology. However, little is known about the incidence, morphologic pattern, and clinical features of spleens involved by amyloidosis. We retrospectively identified 69 spleen amyloid cases typed using a proteomics-based method between 2008 and 2020. The frequency of amyloid types, clinicopathologic features, and distribution of amyloid deposits were assessed. Four amyloid types were detected: immunoglobulin light chain (AL) (N=30; 43.5%); leukocyte chemotactic factor 2 amyloidosis (ALECT2) (N=30; 43.5%); amyloid A (AA) (N=8; 11.6%); and fibrinogen alpha (AFib) (N=1; 1.4%). The splenic amyloid showed 5 distinct distribution patterns: (1) diffuse pattern, exhibited by most AL cases; (2) red pulp pattern, exhibited by most ALECT2 cases; (3) multinodular pattern, seen in subsets of AA and AL-kappa cases; (4) mass-forming pattern, seen in the AFib case; and (5) vascular only, seen in a subset of AA cases. Atraumatic splenic rupture was the most common reason for splenectomy in AL cases, while most ALECT2 spleens were removed incidentally during an unrelated abdominal surgery. Splenomegaly was significantly more common in AA spleens than in AL or ALECT2 spleens and was often the reason for splenectomy in this group. In conclusion, splenic amyloid may be underrecognized as it is often an incidental finding. Although, as expected, many of the spleens were involved by AL amyloidosis, ALECT2 emerged as another common spleen amyloid type. Although the spleen amyloid types exhibited characteristic distribution patterns, proteomics-based typing is warranted as some morphologic overlap still exists. Awareness of ALECT2 as a major spleen amyloid type is important for appropriate diagnostic workup and patient management.

AbstractVulvar lichen sclerosus (VLS) confers approximately 3% risk of malignant transformation to vulvar squamous cell carcinoma (VSCC). We used unbiased proteomic methods to identify differentially expressed proteins in tissue of patients with VLS who developed VSCC compared to those who did not. We used laser capture microdissection‐ and nanoLC‐tandem mass spectrometry to assess protein expression in individuals in normal vulvar tissue (NVT, n = 4), indolent VLS (no VSCC after at least 5 years follow‐up, n = 5) or transforming VSCC (preceding VSCC, n = 5). Interferon‐γ and antigen‐presenting pathways are overexpressed in indolent and transforming VLS compared to NVT. There was differential expression of malignancy‐related proteins in transforming VLS compared to indolent VLS (CAV1 overexpression, AKAP12 underexpression), particularly in the EIF2 translation pathway, which has been previously implicated in carcinogenesis. Results of this study provide additional molecular evidence supporting the concept that VLS is a risk factor for VSCC and highlights possible future biomarkers and/or therapeutic targets.

Anaplastic large cell lymphoma (ALCL) can be classified genetically based on rearrangements (R) of the ALK, TP63, and/or DUSP22 genes. ALK-R defines a specific entity, ALK-positive ALCL, while DUSP22-R and TP63-R define subgroups of ALK-negative ALCLs with distinct clinicopathologic features. ALK-R and TP63-R produce oncogenic fusion proteins that can be detected by immunohistochemistry. ALK immunohistochemistry is an excellent surrogate for ALK-R and screening with p63 immunohistochemistry excludes TP63-R in two third of ALCLs. In contrast, DUSP22-R does not produce a fusion protein and its identification requires fluorescence in situ hybridization. However, DUSP22-R ALCL has a characteristic phenotype including negativity for cytotoxic markers and phospho-STAT3Y705. Recently, we also identified overexpression of the LEF1 transcription factor in DUSP22-R ALCL. Here, we sought to validate this finding and examine models for predicting DUSP22-R using immunohistochemistry for LEF1 and TIA1 or phospho-STAT3Y705. We evaluated these 3 markers in our original discovery cohort (n=45) and in an independent validation cohort (n=46) of ALCLs. The correlation between DUSP22-R and LEF1 expression replicated strongly in the validation cohort (P<0.0001). In addition, we identified and validated a strategy using LEF1 and TIA1 immunohistochemistry that predicted DUSP22-R with positive and negative predictive values of 100% after exclusion of indeterminate cases and would eliminate the need for fluorescence in situ hybridization in 65% of ALK-negative ALCLs. This approach had similar results in identifying DUSP22-R in the related condition, lymphomatoid papulosis. Together with previous data, these findings support a 4-marker immunohistochemistry algorithm using ALK, LEF1, TIA1, and p63 for genetic subtyping of ALCL.

Abstract Multiple Myeloma (MM) is a hematologic malignancy marked by uncontrolled clonal expansion of plasma cells. Previous research has examined single-cell transcriptome profiles of Monoclonal gammopathy of undetermined significance (MGUS) and MM tumor microenvironment (TME) and found that natural killer (NK) cell abundance is elevated in the early stages and correlated with altered chemokine receptor expression. This study suggested the critical role of immune cells on myeloma progression from asymptomatic MGUS to symptomatic MM. Up to date, however, there are no published studies comprehensively comparing tumor and immune populations differences between MM NON-progressors (NPs) and FAST-progressors (FPs) and investigating how clonal plasma cells affect disease progression in a large cohort. Therefore, understanding how tumor and immune cells influence disease progression within symptomatic MM is of great interest.Here, we subjected CD138-negative Bone Marrow Mononuclear cells (BMMC) samples from 418 MM patients to scRNA-seq. From MMRF CoMMpass study (NCT01454297), we also have whole exome sequencing (WES) and bulk RNA-seq from CD138-positive fraction of BMMC samples. Based on time to progressive disease (TTPD), we classified patients into 2 categories. Patients with TTPD less than 18 months were classified as FAST-progressors (FPs), whereas patients with TTPD more than 5 years were classified as NON-progressors (NPs). By analyzing patient genomic alterations and its association with progression, we found that there was a significant association of slow MM progression with t(11;14) (p = 0.048), consistent with previous study. In our preliminary analysis, we profiled 83 CD138-sorted MM bone marrow samples using scRNA-seq. Interestingly, we found plasma cells from samples with the same genetic alterations tend to cluster together, highlighting the important role of genetic drivers in transcriptome profiles of plasma cells. Moreover, integrated analysis of bone marrow samples from 83 MM patients and 4 healthy donors revealed an atypical naïve-B cell subset with enrichment of cells from fast-progressors and partial expression of MS4A1. Differentially expressed genes for this naïve-B cell subset includes KLF9, BCL2L11, JOSD1, and IRS2, etc. Overall, as part of MMRF immune profiling research, this study will help to interrogate how genetic alterations and disease progression interplay MM tumor and TME and provide a sufficiently broad and valuable dataset for systematically characterizing MM at single-cell resolution. Hopefully, this study could identify novel targets for MM immunotherapies, and ultimately identify patients with high risk of fast progression for early intervention in the clinic. Citation Format: Lijun Yao, Tianjiao Wang, Kazuhiro Sato, Reyka Jayasinghe, I-Ling Chiang, Darwin D'souza, William Pilcher, Edgar Gonzalez-Kozlova, Yered Pita-Juarez, Taxiarchis Kourelis, Deon Bryant Doxie, Beena Thomas, Brian Lee, Swati Sharma Bhasin, Upadhyaya Bhaskar, Mark Fiala, Julie Fortier, Travis Dawson, John Leech, Shaji Kumar, Hearn Cho, Seunghee Kim-Schulze, Bee Raj, Stephen Oh, the MMRF Immune Profiling Research Team, John Dipersio, Ravi Vij, Adeeb Rahman, Ionnis Vlachos, Shaadi Mehr, Mark Hamilton, Daniel Auclair, Surendra Dasari, David Avigan, Madhav Dhodapkar, Sacha Gnjatic, Manoj Bhasin, Li Ding. Single-cell transcriptome profiling of multiple myeloma bone marrow samples suggests that disease progression interplays with tumor and tumor microenvironment in The MMRF CoMMpass Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1729.

Abstract IgM MGUS and Waldenstrom Macroglobulinemia (WM) represent a disease spectrum with highly dissimilar therapeutic management ranging from observation to chemoimmunotherapy. The current classification relies solely on clinical features and does not explain the heterogeneity that exists within each of these conditions. To shed light on the biology that may account for the clinical differences, we used bone marrow (BM) CD19+/CD138+ sorted cells and matched BM plasma from 32 patients (pts) (7 IgM MGUS, 25 WM) and 5 healthy controls to perform the first comprehensive multiomics approach including whole exome sequencing, RNA seq, proteomics and metabolomics. Applying principal component analysis to gene expression profiling, most of WM pts clustered together, while a small subset of them grouped separately with MGUS pts, suggesting a biologic dichotomy within WM. The healthy controls formed a distinct group from most WM and MGUS. We then applied a non-negative matrix factorization consensus clustering to the gene expression data and identified three robust clusters. Cluster 1 (C1) included only WM pts, cluster 2 (C2) included both WM and MGUS pts, and cluster 3 (C3) included all controls as well as a small number of WM and MGUS pts. When mutations commonly identified in WM were analyzed, there was no difference among the three groups (excluding controls) in mutation burden of MYD88 L265P and CXCR4. Interestingly, aberrant expression of TNFAIP3 seemed a distinct feature of C1 as deletion of 6q (which encodes for TNFAIP3) and TNFAIP3 mutations were each significantly enriched in C1 (47%) compared to C2 (0%) and C3 (20%; p=0.04). Individual clusters associated with specific transcriptional signature and clinical features. While C1 displayed enrichment of cell growth, downregulation of inflammatory pathways (eg IL6 and IL8 signaling) and aggressive behavior, C2 showed increased inflammatory signaling and cell survival with indolent behavior. C3 had an intermediate feature with combined proliferative and inflammatory signatures. In accordance with the transcriptomic data, the hallmark of C1 was upregulation of proliferation-associated proteins (eg AKT, MAPK) and downregulation of inflammatory proteins (eg IL4, IL10) while the opposite was observed in C2. Once more, C3 confirmed intermediate features with combined upregulation of proliferation and inflammatory proteins. The metabolism was rewired towards fatty acid catabolism in C1, glycolysis in C2 and anabolism in C3. Accordingly, C1 showed undetectable concentration of 3-hydroxybutyric acid as opposed to C2 which had increased levels of malic and lactic acids, as end products of fatty acid oxidation and glycolysis respectively. Those metabolites had intermediate levels in C3. In conclusion, we identified three molecular clusters with distinct clinical, proteomic and metabolomic features, suggesting a potential biologic classification that may have therapeutic implications. Citation Format: Patrizia Mondello, Jonas Paludo, Joseph Novak, Kerstin Wenzl, Shahrzad Jalali, Jordan Krull, Esteban Braggio, Surendra Dasari, Michelle Manske, Jithma Abeykoon, Asher Chanan-Khan, Robert Kyle, Morie Gertz, Zhi Zhang Yang, Anne Novak, Stephen Ansell. Molecular clusters and functional drivers of IgM monoclonal gammopathies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3487.