S171: MOLECULAR CLUSTERS OF IGM MONOCLONAL GAMMOPATHIES PRESENT DISTINCT BIOLOGIC, IMMUNE AND METABOLIC FEATURES

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.

Common Gene Expression Signature of B-Cells of Waldenström Macroglobulinemia (WM) and IgM Monoclonal Gammopathies of Undetermined Significance (IgM MGUS) Compared to Healthy Subjects

To characterise clusters of individuals based on adherence to dietary recommendations and to determine whether changes in Healthy Eating Index (HEI) scores in response to a personalised nutrition (PN) intervention varied between clusters. Food4Me study participants were clustered according to whether their baseline dietary intakes met European dietary recommendations. Changes in HEI scores between baseline and month 6 were compared between clusters and stratified by whether individuals received generalised or PN advice. Pan-European, Internet-based, 6-month randomised controlled trial. Adults aged 18-79 years (n 1480). Individuals in cluster 1 (C1) met all recommended intakes except for red meat, those in cluster 2 (C2) met two recommendations, and those in cluster 3 (C3) and cluster 4 (C4) met one recommendation each. C1 had higher intakes of white fish, beans and lentils and low-fat dairy products and lower percentage energy intake from SFA (P<0·05). C2 consumed less chips and pizza and fried foods than C3 and C4 (P<0·05). C1 were lighter, had lower BMI and waist circumference than C3 and were more physically active than C4 (P<0·05). More individuals in C4 were smokers and wanted to lose weight than in C1 (P<0·05). Individuals who received PN advice in C4 reported greater improvements in HEI compared with C3 and C1 (P<0·05). The cluster where the fewest recommendations were met (C4) reported greater improvements in HEI following a 6-month trial of PN whereas there was no difference between clusters for those randomised to the Control, non-personalised dietary intervention.

Can twin fetuses be numerically clustered characterizing fetal cardiovascular system function?

Immune System Profiling of Waldenstrom Macroglobulinemia (WM) and Immunoglobulin M Monoclonal Gammopathy of Undetermined Significance (IgM MGUS) Using Mass Cytometry (CyTOF)

Immune-related subgroup classification in immune checkpoint blockade (ICB) therapy is largely inconclusive in lung adenocarcinoma (LUAD). First, the single-sample Gene Set Enrichment Analysis (ssGSEA) and K-means algorithms were used to identify immune-based subtypes for the LUAD cohort based on the immunogenomic profiling of 29 immune signatures from The Cancer Genome Atlas (TCGA) database (n = 504). Second, we examined the prognostic and predictive value of immune-based subtypes using bioinformatics analysis. Survival analysis and additional COX proportional hazards regression analysis were conducted for LUAD. Then, the immune score, tumor-infiltrating immune cells (TIICs), and immune checkpoint expression of the three subtypes were analyzed. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) of the differentially expressed genes (DEGs) between three immune-based subtypes were subsequently analyzed for functional enrichment pathways. A total of three immune-based subtypes with distinct immune signatures have been identified for LUAD and designated as cluster 1 (C1), cluster 2 (C2), and cluster 3 (C3). Patients in C3 had higher stromal, immune, and ESTIMATE scores, whereas those in C1 had the opposite. Patients in C1 had an enrichment of macrophages M0 and activation of dendritic cells, whereas tumors in C3 had an enrichment of CD8+ T cells, activation of CD4+ memory T cells, and macrophages M1. C3 had a higher immune cell infiltration and a better survival prognosis than other subtypes. Furthermore, patients in C3 had higher expression levels of immune checkpoint proteins such as PD-L1, PD1, CTLA4, LAG3, IDO1, and HAVCR2. No significant differences were found in cluster TMB scores. We also found that immune-related pathways were enriched in C3. LUAD subtypes based on immune signatures may aid in the development of novel treatment strategies for LUAD.

Simple SummaryIgM monoclonal gammopathy of undetermined significance (IgM MGUS) is an early precursor stage of the rare lymphoma Waldenström Macroglobulinemia (WM). Although comparative gene expression studies on WM, IgM MGUS, and normal B-cells (CTRLs) identified several differentially expressed genes, reliable predictors of progression from IgM MGUS to WM have not yet been identified. We performed a microarray study on CD19+ and CD138+ cells of WM vs. IgM MGUS vs. CTRLs to determine gene signatures for both cell populations. We demonstrated that hematopoietic antigens, cell-adhesion molecules, Wnt-signaling, BCR-signaling, calcium signaling, coagulation cascade, and pathways responsible for cell cycle and proliferation were significantly enriched for genes expressed in B-cells of WM vs. IgM MGUS vs. CTRLs. Interestingly, we showed nine genes which displayed the same expression levels in WM and IgM MGUS compared to CTRLs, suggesting their possible role in the risk of transformation of IgM MGUS to WM.Waldenström Macroglobulinemia (WM) is a B-cell lymphoma characterized by the precursor condition IgM monoclonal gammopathies of undetermined significance (IgM MGUS). We performed a gene expression profiling study to compare the transcriptome signatures of bone marrow (BM) B-cells and plasma cells of 36 WM patients, 13 IgM MGUS cases, and 7 healthy subjects used as controls (CTRLs) by Affymetrix microarray. We determined 2038 differentially expressed genes (DEGs) in CD19+ cells and 29 DEGs genes in CD138+ cells, respectively. The DEGs identified in B-cells were associated with KEGG pathways, mainly involved in hematopoietic cell lineage antigens, cell adhesion/focal adhesion/transmembrane proteins, adherens junctions, Wnt-signaling pathway, BCR-signaling pathway, calcium signaling pathway, complement/coagulation cascade, platelet activation, cytokine-cytokine receptor interactions, and signaling pathways responsible for cell cycle, apoptosis, proliferation and survival. In conclusion, we showed the deregulation of groups of genes belonging to KEGG pathways in the comparison among WM vs. IgM MGUS vs. CTRLs in B-cells. Interestingly, a small set of genes in B-cells displayed a common transcriptome expression profile between WM and IgM MGUS compared to CTRLs, suggesting its possible role in the risk of transformation of IgM MGUS to WM.

BackgroundLong-term care units’ residents do not constitute a homogeneous population. Providing effective care, tailored to individual needs, is crucial in this context. It can be facilitated by suitable tools and methods, which include needs assessment along with the physical, psychological and social aspects of care. We thus applied a cluster approach to identify their putative groupings to enable the provision of tailored care.MethodsThe needs of 242 residents of care homes in four Polish cities (Poznan, Wroclaw, Bialystok and Lublin), aged 75–102 years (184 females), with the Mini-Mental State Examination (MMSE) score ≥ 15 points, were assessed with the CANE (Camberwell Assessment of Need for the Elderly) questionnaire. Their independence in activities of daily living was evaluated by the Barthel Index (BI), and symptoms of depression by the Geriatric Depression Scale (GDS). The results of MMSE, BI and GDS were selected as variables for K-means cluster analysis.ResultsCluster 1 (C1), n = 83, included subjects without dementia according to MMSE (23.7 ± 4.4), with no dependency (BI = 85.8 ± 14.4) and no symptoms of depression (GDS = 3.3 ± 2.0). All subjects of cluster 2 (C2), n = 87, had symptoms of depression (GDS = 8.9 ± 2.1), and their MMSE (21.0 ± 4.0) and BI (79.8 ± 15.1) were lower than those in C1 (p = 0.006 and p = 0.046, respectively). Subjects of cluster 3 (C3), n = 72, had the lowest MMSE (18.3 ± 3.1) and BI (30.6 ± 18,8, p < 0.001 vs. C1 & C2). Their GDS (7.6 ± 2.3) were higher than C1 (p < 0.001) but lower than C2 (p < 0.001). The number of met needs was higher in C2 than in C1 (10.0 ± 3.2 vs 8.2 ± 2.7, p < 0.001), and in C3 (12.1 ± 3.1) than in both C1 and C2 (p < 0.001). The number of unmet needs was higher in C3 than in C1 (1.2 ± 1.5 vs 0.7 ± 1.0, p = 0.015). There were also differences in the patterns of needs between the clusters.ConclusionsClustering seems to be a promising approach for use in long-term care, allowing for more appropriate and optimized care delivery. External validation studies are necessary for generalized recommendations regarding care optimization in various regional perspectives.

Background: Lung squamous cell carcinoma (LUSC) is the second most popular histologic subtype accounting for 25%~30% of lung cancer. Due to the lack of targeted therapies for LUSC, the prognosis is poor and chemotherapy still plays a full role in the treatment of LUSC patients currently. However, a significant proportion of patients showed a bad response to chemotherapy. The development of predictive biomarkers is urgent. We aimed to identify new chemotherapy biomarkers based on genomic alterations. Methods: We retrospectively analyzed DNA sequencing data of 317 LUSC patients (pts) at West China hospital. We collected the clinical features and progression-free survival (PFS) of 35 pts with chemotherapy only. Pts were assigned to different subgroups based on genomic alterations using non-negative matrix factorization (NMF) clustering. Based on the characteristics of the cluster, we then explored clear gene signatures to predict the prognosis of chemotherapy. The clinical information and sequencing data of TCGA LUSC with chemotherapy were used to validate the prognostic value of the signature. Results: The 317 LUSC pts were grouped into 4 clusters characterized by different genomic alterations. Cluster 1 (C1) had 129 pts and was characterized by TP53 alterations. There were 116 pts in cluster 2 (C2) characterized by PIK3CA amplification (amp). Cluster 3 (C3) had 33 pts and was characterized by gene amp of CCND1, FGF3, FGF4, and FGF19. Cluster 4 (C4) was characterized by gene amp of FGFR1, KDR, KIT, and PDGFRA. The 35 pts treated with chemotherapy only were also classified into 4 clusters. C1 was associated with the shortest PFS (hazard ratio (HR), 2.87; 95% confidence interval (CI), 1.15-7.13; p = 0.018) independently of the clinical stage, but C2, C3, and C4 showed no significant difference. In addition, we also found that pts with TP53 loss of function (LOF) alteration had significantly shorter PFS than those without TP53 LOF (wildtype or not LOF, p = 0.029). So we further modified the clustering by TP53 alteration from C1 and gene amp from C2, C3, and C4. Therefore, 35 pts were then grouped into 3 subtypes based on TP53 LOF and gene amp characteristics, and the PFS was significantly different. Pts (n = 8, 23%) with at least one amp of 9 genes (PIK3CA, CCND1, FGF3, FGF4, FGF19, FGFR1, KDR, KIT, and PDGFRA) but no TP53 LOF had the longest PFS (HR, 0.12; 95% CI, 0.02-0.66; p = 0.011). Pts (n = 6) with TP53 LOF but no 9-gene amp had poor survival compared with pts in other subtypes. This gene signature was validated in TCGA pts. The signature of 9-gene amp without TP53 LOF also indicated the best PFS and TP53 LOF without 9-gene amp indicated the worst PFS (p = 0.081). Conclusion: We develop a biomarker signature that consists of 9-gene amp and TP53 LOF to indicate the prognosis of chemotherapy. Our results suggest that 9-gene amp without TP53 LOF in LUSC is a favorable prognostic marker for patients taking chemotherapy. Citation Format: Yuan Tang, Yuli Li, Ting Hou, Lili Jiang, Hongjie Liu, Chunxiao Pan, Weiya Wang, Li Qiu, Yajing Zhang, Guiping Zhang, Ke Zheng. Identification of gene amplification based signature as predictors for chemotherapy in squamous cell carcinoma of the lung. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5470.

Circulating B Cell Clones in Familial Waldenström Macroglobulinemia.

IgM monoclonal gammopathy of undetermined significance (MGUS) and Waldenström macroglobulinemia (WM) represent a disease spectrum with highly varied 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. Further investigation is warranted to shed light on the biology that may account for the clinical differences. We used bone marrow (BM) clonal CD19+ and/or CD138+ sorted cells, matched BM supernatant, and peripheral blood serum from 32 patients (7 MGUS, 25 WM) to perform the first multi-omics approach including whole-exome sequencing, RNA sequencing, proteomics, metabolomics, and mass cytometry. We identified three clusters with distinct pathway activation, immune content, metabolomic, and clinical features. Cluster 1 included only patients with WM and was characterized by transcriptional silencing of genes involved in cell cycle and immune response, enrichment of mitochondrial metabolism, infiltration of senescent T effector memory cells, and aggressive clinical behavior. Genetic/structural alterations of TNFAIP3 were distinct events of this cluster. Cluster 2 comprised both MGUS and WM patients with upregulation of inflammatory response, senescence and glycolysis signatures, increased activated T follicular helper and T regulatory cells, and indolent clinical behavior. Cluster 3 also included both MGUS and WM patients and exhibited intermediate features, including proliferative and inflammatory signaling, as well as glycolysis and mitochondrial metabolism. We have identified three distinct molecular clusters, suggesting a potential biologic classification that may have therapeutic implications.

&lt;div&gt;AbstractPurpose:&lt;p&gt;IgM monoclonal gammopathy of undetermined significance (MGUS) and Waldenström macroglobulinemia (WM) represent a disease spectrum with highly varied 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. Further investigation is warranted to shed light on the biology that may account for the clinical differences.&lt;/p&gt;Experimental Design:&lt;p&gt;We used bone marrow (BM) clonal CD19&lt;sup&gt;+&lt;/sup&gt; and/or CD138&lt;sup&gt;+&lt;/sup&gt; sorted cells, matched BM supernatant, and peripheral blood serum from 32 patients (7 MGUS, 25 WM) to perform the first multi-omics approach including whole-exome sequencing, RNA sequencing, proteomics, metabolomics, and mass cytometry.&lt;/p&gt;Results:&lt;p&gt;We identified three clusters with distinct pathway activation, immune content, metabolomic, and clinical features. Cluster 1 included only patients with WM and was characterized by transcriptional silencing of genes involved in cell cycle and immune response, enrichment of mitochondrial metabolism, infiltration of senescent T effector memory cells, and aggressive clinical behavior. Genetic/structural alterations of &lt;i&gt;TNFAIP3&lt;/i&gt; were distinct events of this cluster. Cluster 2 comprised both MGUS and WM patients with upregulation of inflammatory response, senescence and glycolysis signatures, increased activated T follicular helper and T regulatory cells, and indolent clinical behavior. Cluster 3 also included both MGUS and WM patients and exhibited intermediate features, including proliferative and inflammatory signaling, as well as glycolysis and mitochondrial metabolism.&lt;/p&gt;Conclusions:&lt;p&gt;We have identified three distinct molecular clusters, suggesting a potential biologic classification that may have therapeutic implications.&lt;/p&gt;&lt;/div&gt;

&lt;div&gt;AbstractPurpose:&lt;p&gt;IgM monoclonal gammopathy of undetermined significance (MGUS) and Waldenström macroglobulinemia (WM) represent a disease spectrum with highly varied 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. Further investigation is warranted to shed light on the biology that may account for the clinical differences.&lt;/p&gt;Experimental Design:&lt;p&gt;We used bone marrow (BM) clonal CD19&lt;sup&gt;+&lt;/sup&gt; and/or CD138&lt;sup&gt;+&lt;/sup&gt; sorted cells, matched BM supernatant, and peripheral blood serum from 32 patients (7 MGUS, 25 WM) to perform the first multi-omics approach including whole-exome sequencing, RNA sequencing, proteomics, metabolomics, and mass cytometry.&lt;/p&gt;Results:&lt;p&gt;We identified three clusters with distinct pathway activation, immune content, metabolomic, and clinical features. Cluster 1 included only patients with WM and was characterized by transcriptional silencing of genes involved in cell cycle and immune response, enrichment of mitochondrial metabolism, infiltration of senescent T effector memory cells, and aggressive clinical behavior. Genetic/structural alterations of &lt;i&gt;TNFAIP3&lt;/i&gt; were distinct events of this cluster. Cluster 2 comprised both MGUS and WM patients with upregulation of inflammatory response, senescence and glycolysis signatures, increased activated T follicular helper and T regulatory cells, and indolent clinical behavior. Cluster 3 also included both MGUS and WM patients and exhibited intermediate features, including proliferative and inflammatory signaling, as well as glycolysis and mitochondrial metabolism.&lt;/p&gt;Conclusions:&lt;p&gt;We have identified three distinct molecular clusters, suggesting a potential biologic classification that may have therapeutic implications.&lt;/p&gt;&lt;/div&gt;

BackgroundDementia with Lewy bodies (DLB) is a neurodegenerative disorder that presents with a variety of clinical symptoms. Part of the clinical heterogeneity within DLB has been related to the atrophy/sparing of the hippocampus. We extended that previous research by investigating whether different atrophy patterns exist in DLB, beyond and above the atrophy/sparing of the hippocampus, and whether those patterns contribute to the clinical heterogeneity in DLB. We aimed to identify DLB atrophy subtypes using a hypothesis‐free data‐driven clustering approach based on regional gray matter (GM) volumes and characterize the resulting subtypes across key measures.MethodWe included data from three centers of the European DLB consortium. A high‐resolution 3D T1‐weigthed magnetization prepared rapid gradient echo (MPRAGE) sequence was acquired for 97 DLB patients. Eighty‐four cortical regions and 12 subcortical regions from Mayo Clinic Adult Lifespan Template (https://www.nitrc.org/projects/mcalt/) atlases were obtained. Clusters of DLB patients were then determined using the random forest method. Between‐group differences in key demographic, clinical, MRI volumes and cerebrospinal fluid biomarkers (CSF) (amyloid‐beta, phosphorylated‐tau) were performed for clusters characterization.ResultWe identified three subtypes of DLB patients, with distinct patterns of GM volumes and differences in several clinical and demographic measures. Cluster 1 (C1) included 32 DLB patients (33%), cluster 2 (C2) included 29 DLB patients (30%), and cluster 3 (C3) included 36 DLB patients (37%). The clusters differed in age, with C1 being significantly older (72±8.6) than C3 (66±9.5) (F=3.93, p=0.02). C1 was characterized by lower volumes in fronto‐temporal regions and had a higher frequency of visual hallucinations (68%, vs. C2 35%). C2 showed lower volumes in occipital regions. C3 had higher GM volumes overall compared with the other two clusters and presented with a higher frequency of cognitive fluctuations (91%, vs. C1 67%). There were no differences between groups in CSF biomarkers. These results were independent of cluster differences in age and global GM volume.ConclusionThere are distinct patterns of brain atrophy in patients with DLB. These patterns seem to differentially contribute to the frequencies of visual hallucinations and cognitive fluctuations, independently of differences in age and global GM volume across subtypes.

IntroductionPsychiatric patients often are self-stigmatized and hardly involve in the treatment.ObjectivesAssociations of self-stigmatizing beliefs in psychiatric inpatients and their treatment motivation.Methods63 inpatients; ICD-10: F2–65%, F3–13%, F4+F6–14%, F06–8%; mean age 34±13, illness duration 12±11 years. Treatment Motivation Assessment Questionnaire (TMAQ), Internalized Stigma of Mental Illness scale (ISMI); K-mean cluster analysis; dispersion analyses; p≤0.05.Results18 patients of cluster 1 (C1) demonstrated explicit self-stigmatization. In comparison with 25 subjects from cluster 3 (C3) stigmatized patients (C1) had higher levels of overall ISMI scores (2.9±0.3) caused by alienation (3.1±0.5), stereotype endorsement (2.5±0.5), social withdrawal (2.7±0.4), and discrimination experience (2.7±0.4). 20 patients of cluster 2 (C2) had an implicit stigma. They were more self-stigmatized (ISMI score 2.7±0.3) in contrast with subjects from cluster 3 (1.9±0.2) due to a lower level of stigma resistance (C2: 3.8±0.5 and C3 3.1±0.6 – reverse scores). Patients with implicit self-stigma (C2) had the lowest intensity of treatment motivation (Z-scores -1.2±0.6) compering with others (C1 and C3) due to the lowest TMAQ factor 1 (reliance on own knowledge and skills to cope with the disorder: -1.0±0.6) and factor 4 (willingness to cooperate with doctor: -0.9±1.0). Differences between explicitly and implicitly stigmatized patients manifested also in lower TMAQ factor 3 for the second group (awareness of the psychological mechanism of maladaptation: -0.5±0.9).ConclusionsDespite alienation, stereotype endorsement, social withdrawal, discrimination experience some patients could sustain stigma due to cooperation with doctors and reliance on their own knowledge and skills to cope with illness.