bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract PS18-10: Tumor-Infiltrating Lymphocytes and Breast Cancer Mortality in Racially and Ethnically Diverse Participants of the Northern California Breast Cancer Family Registry
Authors: Ransohoff Julia , Miller Iain , Koo Jocelym , Joshi Vishal , Kurian Allison , Allison Kimberly , John Esther , Telli Melinda
Published: May 2024

Purpose:

Greater stromal tumor-infiltrating lymphocyte (sTIL) percentage in pre-treatment breast tumor specimens is associated with superior response to neoadjuvant chemotherapy and survival. We hypothesized that sTIL-survival associations vary by race and ethnicity and mediate survival disparities.

Patients and Methods: We evaluated pre-treatment percentages of sTILs in deciles for 284 women enrolled in the Northern California Breast Cancer Family Registry and diagnosed with a first primary invasive breast cancer from 1995-2005. We assessed associations of continuous sTIL scores and lymphocyte-predominant breast cancer (LPBC, defined as ≥50% lymphocytic infiltration of tumor stroma or cell nests) with clinical and epidemiologic characteristics using regression analysis and with breast cancer-specific mortality (BCM) and overall mortality (OM) using Cox proportional hazards regression.

Results:

The cohort was diverse (64% from racially and ethnically minoritized populations) with near-complete (98%) germline BRCA1/2 testing and long-term follow-up (average 16.2 years, range: 1.3-26.7). In multivariable analyses, higher sTIL score was associated with reduced BCM [LPBC versus non-LPBC: HR=0.44 (95% confidence interval 0.20-0.98); and per decile increase in sTIL score: HR=0.80 (0.69-0.93)], with the strongest association in the subset of patients with hormone receptor-negative disease [HR=0.71 (0.57-0.88) and HR=0.37 (0.14-0.94), respectively]. While there was no significant difference in sTIL score between racial and ethnic groups, the continuous sTIL-survival association was statistically significant among non-Hispanic White [HR=0.73 (0.57-0.94)] and Asian American [HR=0.56 (0.35-0.89)] women but was not seen among African American and Hispanic women.

Conclusion:

We identified novel sTIL-BCM differences by race and ethnicity, with better survival associated with sTIL enrichment among non-Hispanic White and Asian American but not among African American or Hispanic women. Additional studies are needed to determine whether survival and particularly the response to immunotherapy are differentially mediated by immune factors between racial and ethnic groups.

Multivariable Cox Proportional Hazards Regression Models of Breast Cancer-Specific and Overall Mortality.

Citation Format: Julia Ransohoff, Iain Miller, Jocelym Koo, Vishal Joshi, Allison Kurian, Kimberly Allison, Esther John, Melinda Telli. Tumor-Infiltrating Lymphocytes and Breast Cancer Mortality in Racially and Ethnically Diverse Participants of the Northern California Breast Cancer Family Registry [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS18-10.
Abstract SoA2-02: Implications of therapy induced senescence in breast cancer
Authors: Jackson J.
Published: May 2024

The goal of breast cancer treatment is to cause cellular stress sufficient to kill and eliminate the tumor cells. Unfortunately, in many cases cancer cells survive and are not removed by surgery and thus can cause relapse and eventual mortality. Surviving cells have necessarily avoided both intrinsic (e.g., apoptosis) and extrinsic (e.g., immune surveillance) mechanisms of death. Studies over the last 20 years have shown that chemotherapy-treated breast cancer cells can evade cell death by activating programs of cellular senescence mediated by the tumor suppressor p53. While p53 can induce apoptosis in response to stress in some cell types, in breast cancer, p53 preferentially induces cell cycle arrest and senescence in response to chemotherapy. Data show that patients with breast cancers that are wild type for TP53 have a much lower probability of being eradicated by chemotherapy, and have a much shorter survival, compared to patients with TP53 mutant tumors. Human and mouse mammary tumors induce many markers of senescence after chemotherapy treatment, including those associated with cell cycle arrest and the senescence associated secretory phenotype (SASP). These arrested tumors evade death from mitotic catastrophe and can block apoptotic programs via elevated activity of BCL2 family members. More recent studies have addressed how induction of senescence deters immune surveillance. Breast cancer cells exposed to chemotherapy reorganize chromatin structure that amplifies stromal derived signals that stimulate expression of many immune genes, including checkpoint ligands such as PD-L1 and Galectin-9. Further, p53 can directly transactivate other immune modulatory genes such as CD80. Collectively, these properties of senescent cells enable their persistence following treatment and contribute to their potential to drive relapse. These same properties, however, can also be exploited as vulnerabilities to therapeutics such as senolytic drugs that target reliance on BCL2 family members or immunotherapies that target PD-L1 expression.

Citation Format: J. Jackson. Implications of therapy induced senescence in breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr SoA2-02.
Abstract TC-01: Baby-TAM Impact on disease progression
Authors: Cuzick J. , Hall P.
Published: May 2024

Professor Hall will have reviewed his studies on the impact of lower doses of tamoxifen on changes in breast density, an important risk factor. Here I will review the work of Professor Decensi’s team on the ability of 5mg/d of tamoxifen (baby-Tam) on the progression rate of DCIS (69%) and other intraepithelial lesions (11% LCIS, 20% atypical ductal hyperplasia). This trial involved 500 pre- and postmenopausal women randomized equally between baby-Tam and placebo with a 9.7 year median follow up. All breast cancer progression (invasive (77%) and DCIS (23%)) was reduced by 42% (25 vs 41 events, P = 0.03) and contralateral tumours by 64% (6 vs 16 events, P = 0.025). No significant increase was seen in any side effect (Table). I will also briefly discuss their new award for a project to compare baby Tam to baby exemestane in a randomized trial in a similar population as above, initially for side effects, but also subsequently for efficacy. Professor Hall will have reviewed his studies on the impact of lower doses of tamoxifen on changes in breast density, an important risk factor. Here I will review the work of Professor Decensi’s team on the ability of 5mg/d of tamoxifen (baby-Tam) on the progression rate of DCIS (69%) and other intraepithelial lesions (11% LCIS, 20% atypical ductal hyperplasia). This trial involved 500 pre- and postmenopausal women randomized equally between baby-Tam and placebo with a 9.7 year median follow up. All breast cancer progression (invasive (77%) and DCIS (23%)) was reduced by 42% (25 vs 41 events, P = 0.03) and contralateral tumours by 64% (6 vs 16 events, P = 0.025). No significant increase was seen in any side effect (Table). I will also briefly discuss their new award for a project to compare baby Tam to baby exemestane in a randomized trial in a similar population as above, initially for side effects, but also subsequently for efficacy.

Citation Format: J. Cuzick, P. Hall. Baby-TAM Impact on disease progression [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr TC-01.
Abstract TC-02: When to do a window trial
Authors: Dowsett M. , Hurvitz S.
Published: May 2024

The window of opportunity in the short time between diagnosis and surgery for primary breast cancer has been exploited in trials of many endocrine agents. In these cases the therapeutic effect is antiproliferative and immunohistochemical detection of changes in Ki67 are considered a valid biomarker of likely long term efficacy. Trials have also been extended to assessment of inhibitors of growth factor receptors (eg lapatinib) and COX2 inhibitors. In these circumstances the mode of action is not purely inhibition of proliferation such that while changes in Ki67 may be of interest they should not be taken as necessarily reflecting the presence or absence of efficacy. It is also important to recognise that it may take longer than the time window available to get to a pharmacodynamic steady state. This is reflected by data from studies of tamoxifen and of GnRH analogues in premenopausal women. As well as being a window for assessing the biologic effectiveness of new agents it has been used as a means of assessing the prognosis of patients taking an established drug such as an aromatase inhibitor (AI) in the POETIC and an AI or tamoxifen in the ADAPT trial.

Citation Format: M. Dowsett, S. Hurvitz. When to do a window trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr TC-02.
Abstract Wrk1-01: Agnostic trials in the field of targeted therapies
Authors: Subbiah V.
Published: May 2024

Tumor-agnostic cancer therapy represents a significant shift in the field of precision oncology. It differs from conventional cancer treatments, which typically focus on specific tumor types, such as breast cancer, lung cancer, renal cell cancer, and others. This innovative approach brings hope to cancer patients by recognizing that identical genetic abnormalities can drive cancer in various parts of the body. The approvals of these therapies have introduced alternative treatment options, particularly for patients with advanced cancers and rare malignancies. Currently, six medicines have received US FDA approval for use in patients with solid tumors harboring one of five specific biomarkers. In this presentation, I will delve into the current landscape of these tissue-agnostic cancer therapies, providing a comprehensive exploration of the relevant clinical data that can enhance our understanding of these groundbreaking treatments.

Citation Format: V. Subbiah. Agnostic trials in the field of targeted therapies [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr Wrk1-01.
Figure S2 from Oncogenic GNAS Uses PKA-Dependent and Independent Mechanisms to Induce Cell Proliferation in Human Pancreatic Ductal and Acinar Organoids
Authors: Desai Ridhdhi , Huang Ling , Gonzalez Raul S. , Muthuswamy Senthil K.
Published: May 2024

IHC images of mouse sections
Figure S1 from Oncogenic GNAS Uses PKA-Dependent and Independent Mechanisms to Induce Cell Proliferation in Human Pancreatic Ductal and Acinar Organoids
Authors: Desai Ridhdhi , Huang Ling , Gonzalez Raul S. , Muthuswamy Senthil K.
Published: May 2024

RNA expression of ductal and acinar markers and GNAS-mediated PKA activity
Supplementary Figure 4 from ROR2/Wnt5a Signaling Regulates Directional Cell Migration and Early Tumor Cell Invasion in Ovarian Cancer
Authors: Grither Whitney R. , Baker Breanna , Morikis Vasilios A. , Ilagan Ma. Xenia G. , Fuh Katherine C. , Longmore Gregory D.
Published: May 2024

Microfluidic device design and vector plots
Supplementary Figure 1 from ROR2/Wnt5a Signaling Regulates Directional Cell Migration and Early Tumor Cell Invasion in Ovarian Cancer
Authors: Grither Whitney R. , Baker Breanna , Morikis Vasilios A. , Ilagan Ma. Xenia G. , Fuh Katherine C. , Longmore Gregory D.
Published: May 2024

Western blots of siRNA depletion and OVCAR8 adhesion
Supplemental Table 4 from ROR2/Wnt5a Signaling Regulates Directional Cell Migration and Early Tumor Cell Invasion in Ovarian Cancer
Authors: Grither Whitney R. , Baker Breanna , Morikis Vasilios A. , Ilagan Ma. Xenia G. , Fuh Katherine C. , Longmore Gregory D.
Published: May 2024

Supplemental Table 4. screen raw data
Supplemental Table 2 from ROR2/Wnt5a Signaling Regulates Directional Cell Migration and Early Tumor Cell Invasion in Ovarian Cancer
Authors: Grither Whitney R. , Baker Breanna , Morikis Vasilios A. , Ilagan Ma. Xenia G. , Fuh Katherine C. , Longmore Gregory D.
Published: May 2024

Supplemental Table 2. shRNA sequences
Supplemental Table 1 from ROR2/Wnt5a Signaling Regulates Directional Cell Migration and Early Tumor Cell Invasion in Ovarian Cancer
Authors: Grither Whitney R. , Baker Breanna , Morikis Vasilios A. , Ilagan Ma. Xenia G. , Fuh Katherine C. , Longmore Gregory D.
Published: May 2024

Supplemental Table 1. antibody list
Supplementary Table 1 from SCUBE3 Exerts a Tumor-Promoting Effect in Tongue Squamous Cell Carcinoma by Promoting CEBPA Binding to the CCL2 Promoter
Authors: Zhu Minhui , Ma Yi , Wang Wei , Li Meng , Chen Shicai , Liu Fei , Shi Xiaoqiong , Bi Hongsen , Zhang Chen , Nie Fangfei , Zheng Hongliang , Zhang Caiyun
Published: May 2024

Table S1. The shRNA target sequences and scramble sequence (NC).
Supplementary Table 9 from Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts
Authors: Sychev Zoi E. , Day Abderrahman , Bergom Hannah E. , Larson Gabrianne , Ali Atef , Ludwig Megan , Boytim Ella , Coleman Ilsa , Corey Eva , Plymate Stephen R. , Nelson Peter S. , Hwang Justin H. , Drake Justin M.
Published: May 2024

Supplementary Table 9. LuCaP Phosphoproteome VSN ROTS NE vs AdCa
Supplementary Table 7 from Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts
Authors: Sychev Zoi E. , Day Abderrahman , Bergom Hannah E. , Larson Gabrianne , Ali Atef , Ludwig Megan , Boytim Ella , Coleman Ilsa , Corey Eva , Plymate Stephen R. , Nelson Peter S. , Hwang Justin H. , Drake Justin M.
Published: May 2024

Supplementary Table 7. LuCaP Phosphoproteome Imputed Data
Supplementary Table 5 from Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts
Authors: Sychev Zoi E. , Day Abderrahman , Bergom Hannah E. , Larson Gabrianne , Ali Atef , Ludwig Megan , Boytim Ella , Coleman Ilsa , Corey Eva , Plymate Stephen R. , Nelson Peter S. , Hwang Justin H. , Drake Justin M.
Published: May 2024

Supplementary Table 5. LuCaP Proteome GSEA Pathways
Supplementary Table 28 from Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts
Authors: Sychev Zoi E. , Day Abderrahman , Bergom Hannah E. , Larson Gabrianne , Ali Atef , Ludwig Megan , Boytim Ella , Coleman Ilsa , Corey Eva , Plymate Stephen R. , Nelson Peter S. , Hwang Justin H. , Drake Justin M.
Published: May 2024

Supplementary Table 28. LuCaP Phosphoproteome VSN Normalized z-scores
Supplementary Table 23 from Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts
Authors: Sychev Zoi E. , Day Abderrahman , Bergom Hannah E. , Larson Gabrianne , Ali Atef , Ludwig Megan , Boytim Ella , Coleman Ilsa , Corey Eva , Plymate Stephen R. , Nelson Peter S. , Hwang Justin H. , Drake Justin M.
Published: May 2024

Supplementary Table 23. LuCaP Phosphoproteome VSN Normalized Differential Expression ROTS AdCa CR vs AdCa NCR
Supplementary Figure 5 from Coregulation of NDC80 Complex Subunits Determines the Fidelity of the Spindle-Assembly Checkpoint and Mitosis
Authors: Kim Sehong , Lau Thomas T.Y. , Liao Man Kit , Ma Hoi Tang , Poon Randy Y.C.
Published: May 2024

Figure S5. Depletion of SPC24 reduces the stability of other subunits of the NDC80C.
Supplementary Table 21 from Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts
Authors: Sychev Zoi E. , Day Abderrahman , Bergom Hannah E. , Larson Gabrianne , Ali Atef , Ludwig Megan , Boytim Ella , Coleman Ilsa , Corey Eva , Plymate Stephen R. , Nelson Peter S. , Hwang Justin H. , Drake Justin M.
Published: May 2024

Supplementary Table 21. LuCaP Phosphoproteome VSN Normalized Differential Functional Expression ROTS AdCa vs NE
Supplementary Figure 3 from Coregulation of NDC80 Complex Subunits Determines the Fidelity of the Spindle-Assembly Checkpoint and Mitosis
Authors: Kim Sehong , Lau Thomas T.Y. , Liao Man Kit , Ma Hoi Tang , Poon Randy Y.C.
Published: May 2024

Figure S3. Mitotic arrest in SPC24-depleted cells correlates with the expression of NDC80C subunits.
Supplementary Figure 2 from Coregulation of NDC80 Complex Subunits Determines the Fidelity of the Spindle-Assembly Checkpoint and Mitosis
Authors: Kim Sehong , Lau Thomas T.Y. , Liao Man Kit , Ma Hoi Tang , Poon Randy Y.C.
Published: May 2024

Figure S2. SPC24 is required for the formation of stable microtubules during mitosis.
Supplementary Figure 1 from Coregulation of NDC80 Complex Subunits Determines the Fidelity of the Spindle-Assembly Checkpoint and Mitosis
Authors: Kim Sehong , Lau Thomas T.Y. , Liao Man Kit , Ma Hoi Tang , Poon Randy Y.C.
Published: May 2024

Figure S1. The effects of different concentrations of IAA on the destruction of mAIDSPC24.
Supplementary Table 19 from Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts
Authors: Sychev Zoi E. , Day Abderrahman , Bergom Hannah E. , Larson Gabrianne , Ali Atef , Ludwig Megan , Boytim Ella , Coleman Ilsa , Corey Eva , Plymate Stephen R. , Nelson Peter S. , Hwang Justin H. , Drake Justin M.
Published: May 2024

Supplementary Table 19. LuCaP Phosphoproteome VSN Normalized Differential Expression ROTS AdCa NCR vs NE
Supplementary Table 18 from Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts
Authors: Sychev Zoi E. , Day Abderrahman , Bergom Hannah E. , Larson Gabrianne , Ali Atef , Ludwig Megan , Boytim Ella , Coleman Ilsa , Corey Eva , Plymate Stephen R. , Nelson Peter S. , Hwang Justin H. , Drake Justin M.
Published: May 2024

Supplementary Table 18. LuCaP Proteome VSN Normalized Differential Expression ROTS AdCa CR vs NE
Supplementary Table 16 from Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts
Authors: Sychev Zoi E. , Day Abderrahman , Bergom Hannah E. , Larson Gabrianne , Ali Atef , Ludwig Megan , Boytim Ella , Coleman Ilsa , Corey Eva , Plymate Stephen R. , Nelson Peter S. , Hwang Justin H. , Drake Justin M.
Published: May 2024

Supplementary Table 16. LuCaP AdCa Functional Proteome
Supplementary Table 10 from Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts
Authors: Sychev Zoi E. , Day Abderrahman , Bergom Hannah E. , Larson Gabrianne , Ali Atef , Ludwig Megan , Boytim Ella , Coleman Ilsa , Corey Eva , Plymate Stephen R. , Nelson Peter S. , Hwang Justin H. , Drake Justin M.
Published: May 2024

Supplementary Table 10. LuCaP Phosphoproteome Upstream Map Quantile Normalized and Log Transformed for KSEA Analysis
Supplementary Table 1 from An Endosomal Acid-Regulatory Feedback System Rewires Cytosolic cAMP Metabolism and Drives Tumor Progression
Authors: Prasad Hari , Mandal Susmita , Mathew John Kandam Kulathu , Cherukunnath Aparna , Duddu Atchuta Srinivas , Banerjee Mallar , Ramani Harini , Bhat Ramray , Jolly Mohit Kumar , Visweswariah Sandhya S.
Published: May 2024

Supplemental Table 1 shows the parameter values for the mathematical model of endosomal pH.
Supplementary Table 1 from Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts
Authors: Sychev Zoi E. , Day Abderrahman , Bergom Hannah E. , Larson Gabrianne , Ali Atef , Ludwig Megan , Boytim Ella , Coleman Ilsa , Corey Eva , Plymate Stephen R. , Nelson Peter S. , Hwang Justin H. , Drake Justin M.
Published: May 2024

Supplementary Table 1. Description of PDX LuCaP Tumors with Pathology
Supplementary Figure 7 from An Endosomal Acid-Regulatory Feedback System Rewires Cytosolic cAMP Metabolism and Drives Tumor Progression
Authors: Prasad Hari , Mandal Susmita , Mathew John Kandam Kulathu , Cherukunnath Aparna , Duddu Atchuta Srinivas , Banerjee Mallar , Ramani Harini , Bhat Ramray , Jolly Mohit Kumar , Visweswariah Sandhya S.
Published: May 2024

Supplementary Figure 7 shows data from Ingenuity Pathway Analysis demonstrating that cyclic AMP signaling is the top upstream regulator controlled by NHE9.
Supplementary Figure 10 from An Endosomal Acid-Regulatory Feedback System Rewires Cytosolic cAMP Metabolism and Drives Tumor Progression
Authors: Prasad Hari , Mandal Susmita , Mathew John Kandam Kulathu , Cherukunnath Aparna , Duddu Atchuta Srinivas , Banerjee Mallar , Ramani Harini , Bhat Ramray , Jolly Mohit Kumar , Visweswariah Sandhya S.
Published: May 2024

Supplementary Figure 10 shows the methylation profile of NHE9 promoter in colorectal cancer.
Data from Oncogenic GNAS Uses PKA-Dependent and Independent Mechanisms to Induce Cell Proliferation in Human Pancreatic Ductal and Acinar Organoids
Authors: Desai Ridhdhi , Huang Ling , Gonzalez Raul S. , Muthuswamy Senthil K.
Published: May 2024

Abstract
Ductal and acinar pancreatic organoids are promising models for the study of pancreatic diseases. Genome sequencing studies have revealed that mutations in a G-protein (GNASR201C) are exclusively observed in intraductal papillary mucinous neoplasms (IPMN). The biological mechanisms by which GNASR201C affects the ductal and acinar exocrine pancreas are unclear. Here, we use human stem-cell-derived pancreatic ductal and acinar organoids and demonstrate that GNASR201C was more effective in inducing proliferation in ductal organoids compared with acinar organoids. Surprisingly, GNASR201C-induced cell proliferation was protein kinase A (PKA)-independent in ductal organoids and an immortalized ductal epithelial cell line. Co-expression of oncogenic KRASG12V and GNASR201C retained PKA-independence in ductal organoids to stimulate cell proliferation. Thus, we identify cell lineage-specific roles for PKA signaling in GNASR201C-driven cell proliferation in precancerous lesions and report the development of a human pancreatic ductal organoid model system to investigate mechanisms regulating GNASR201C-induced IPMNs.
Implications:
The study identifies an opportunity to discover a PKA-independent pathway downstream of oncogene GNAS for managing IPMN lesions and their progression to PDAC.
Data from SCUBE3 Exerts a Tumor-Promoting Effect in Tongue Squamous Cell Carcinoma by Promoting CEBPA Binding to the CCL2 Promoter
Authors: Zhu Minhui , Ma Yi , Wang Wei , Li Meng , Chen Shicai , Liu Fei , Shi Xiaoqiong , Bi Hongsen , Zhang Chen , Nie Fangfei , Zheng Hongliang , Zhang Caiyun
Published: May 2024

Abstract
Tongue squamous cell carcinoma (TSCC) is the main pathologic subtype of oral cancer, and the current therapeutic effect is far from satisfactory. The signal peptide-CUB-EGF domain-containing protein 3 (SCUBE3) has been shown to be a tumor-promoting factor in several malignancies. However, little is known about the role of SCUBE3 in TSCC. In this study, we identified that SCUBE3 was highly expressed in TSCC. Clinically, high expression of SCUBE3 was positively associated with tumor stage and T stage of TSCC. Functionally, SCUBE3 silence remarkably restrained cell proliferation, migration, and invasion, induced apoptosis as well as cell cycle arrest in G2-phase, and weakened the tumorigenicity of TSCC cells in vivo. Mechanistically, SCUBE3 promoted the direct binding of CCAAT enhancer binding protein alpha (CEBPA) to C-C motif chemokine ligand 2 (CCL2) promoter in TSCC cells. Interestingly, CCL2 overexpression partially reversed the inhibitory effect of SCUBE3 deficiency on TSCC cell viability and migration. Moreover, STAT3 signaling contributed to CCL2-mediated phenotypes in TSCC cells.
Implications:
Our data revealed a tumor-promoting role for SCUBE3 in TSCC via the CEBPA/CCL2/STAT3 axis, which provided new insight into novel potential therapeutic target for TSCC.
Data from Coregulation of NDC80 Complex Subunits Determines the Fidelity of the Spindle-Assembly Checkpoint and Mitosis
Authors: Kim Sehong , Lau Thomas T.Y. , Liao Man Kit , Ma Hoi Tang , Poon Randy Y.C.
Published: May 2024

Abstract
NDC80 complex (NDC80C) is composed of four subunits (SPC24, SPC25, NDC80, and NUF2) and is vital for kinetochore–microtubule (KT–MT) attachment during mitosis. Paradoxically, NDC80C also functions in the activation of the spindle-assembly checkpoint (SAC). This raises an interesting question regarding how mitosis is regulated when NDC80C levels are compromised. Using a degron-mediated depletion system, we found that acute silencing of SPC24 triggered a transient mitotic arrest followed by mitotic slippage. SPC24-deficient cells were unable to sustain SAC activation despite the loss of KT–MT interaction. Intriguingly, our results revealed that other subunits of the NDC80C were co-downregulated with SPC24 at a posttranslational level. Silencing any individual subunit of NDC80C likewise reduced the expression of the entire complex. We found that the SPC24–SPC25 and NDC80–NUF2 subcomplexes could be individually stabilized using ectopically expressed subunits. The synergism of SPC24 downregulation with drugs that promote either mitotic arrest or mitotic slippage further underscored the dual roles of NDC80C in KT–MT interaction and SAC maintenance. The tight coordinated regulation of NDC80C subunits suggests that targeting individual subunits could disrupt mitotic progression and provide new avenues for therapeutic intervention.
Implications:
These results highlight the tight coordinated regulation of NDC80C subunits and their potential as targets for antimitotic therapies.
Data from An Endosomal Acid-Regulatory Feedback System Rewires Cytosolic cAMP Metabolism and Drives Tumor Progression
Authors: Prasad Hari , Mandal Susmita , Mathew John Kandam Kulathu , Cherukunnath Aparna , Duddu Atchuta Srinivas , Banerjee Mallar , Ramani Harini , Bhat Ramray , Jolly Mohit Kumar , Visweswariah Sandhya S.
Published: May 2024

Abstract
Although suppressed cAMP levels have been linked to cancer for nearly five decades, the molecular basis remains uncertain. Here, we identify endosomal pH as a novel regulator of cytosolic cAMP homeostasis and a promoter of transformed phenotypic traits in colorectal cancer. Combining experiments and computational analysis, we show that the Na+/H+ exchanger NHE9 contributes to proton leak and causes luminal alkalinization, which induces resting [Ca2+], and in consequence, represses cAMP levels, creating a feedback loop that echoes nutrient deprivation or hypoxia. Higher NHE9 expression in cancer epithelia is associated with a hybrid epithelial–mesenchymal (E/M) state, poor prognosis, tumor budding, and invasive growth in vitro and in vivo. These findings point to NHE9-mediated cAMP suppression as a pseudostarvation-induced invasion state and potential therapeutic vulnerability in colorectal cancer. Our observations lay the groundwork for future research into the complexities of endosome-driven metabolic reprogramming and phenotype switching and the biology of cancer progression.
Implications:
Endosomal pH regulator NHE9 actively controls cytosolic Ca2+ levels to downregulate the adenylate cyclase–cAMP system, enabling colorectal cancer cells to acquire hybrid E/M characteristics and promoting metastatic progression.
Supplementary Table S5 from Examining the Association between Abstinence from Smoking and Healthcare Costs among Patients with Cancer
Authors: Kypriotakis George , Kim Seokhun , Karam-Hage Maher , Robinson Jason D. , Minnix Jennifer A. , Blalock Janice A. , Cui Yong , Beneventi Diane , Kim Bumyang , Pan I.-Wen , Shih Ya-Chen Tina , Cinciripini Paul M.
Published: May 2024

Supplementary Table S5: Insurance class for all patients
Supplementary Table S1 from Examining the Association between Abstinence from Smoking and Healthcare Costs among Patients with Cancer
Authors: Kypriotakis George , Kim Seokhun , Karam-Hage Maher , Robinson Jason D. , Minnix Jennifer A. , Blalock Janice A. , Cui Yong , Beneventi Diane , Kim Bumyang , Pan I.-Wen , Shih Ya-Chen Tina , Cinciripini Paul M.
Published: May 2024

Supplementary Table S1: Definition of “Treatment”
Supplementary Table S1 from Germline and Somatic Fumarate Hydratase Testing in Atypical Uterine Leiomyomata
Authors: Kipnis Lindsay M. , Breen Katelyn M. , Koeller Diane R. , Levine Alison Schwartz , Yang Zelei , Jun Hyeji , Tayob Nabihah , Stokes Samantha M. , Hayes Connor P. , Ghazani Arezou A. , Hill Sarah J. , Rana Huma Q.
Published: May 2024

Supplementary Table S1. List of FH variants detected in the 49 patients with atypical uterine leiomyomata with germline genetic testing from the cohort
Supplementary Materials and Methods from Germline and Somatic Fumarate Hydratase Testing in Atypical Uterine Leiomyomata
Authors: Kipnis Lindsay M. , Breen Katelyn M. , Koeller Diane R. , Levine Alison Schwartz , Yang Zelei , Jun Hyeji , Tayob Nabihah , Stokes Samantha M. , Hayes Connor P. , Ghazani Arezou A. , Hill Sarah J. , Rana Huma Q.
Published: May 2024

Supplementary Materials and Methods
Supplementary Table S5 from Combination of an Autoantibody Panel and Alpha-Fetoprotein for Early Detection of Hepatitis B Virus-Associated Hepatocellular Carcinoma
Authors: Shen Yajing , Chen Jiajun , Wu Jinyu , Li Tiandong , Yi Chuncheng , Wang Keyan , Wang Peng , Sun Changqing , Ye Hua
Published: May 2024

Supplementary Table S5: All data are derived from the training set. The performance evaluation of this panel in an AUC of 0.788 (95% CI: 0.733-0.843), with a sensitivity of 62.9% and a specificity of 80.9%. The AUC for identifying HBV-HCC patients from HBV-LC patients was 0.646 (95% CI: 0.576-0.716), with a sensitivity of 31.0% and a specificity of 83.9%. This panel showed superior diagnostic efficiency in identifying early HBV-HCC compared with AFP, with an AUC of 0.856 (95% CI: 0.761-0.924) for this panel and 0.652 (0.536-0.757) for AFP (P=0.0026).
Supplementary Table S4 from Combination of an Autoantibody Panel and Alpha-Fetoprotein for Early Detection of Hepatitis B Virus-Associated Hepatocellular Carcinoma
Authors: Shen Yajing , Chen Jiajun , Wu Jinyu , Li Tiandong , Yi Chuncheng , Wang Keyan , Wang Peng , Sun Changqing , Ye Hua
Published: May 2024

Supplementary Table S4: The AUC of these four TAAbs for identifying HBV-HCC patients from CHB patients ranged from 0.693-0.739. Among them, anti-DUSP6 showed the highest diagnostic ability, with an AUC of 0.739 (95% CI [confidence interval]: 0.694-0.785). The diagnostic capability of anti-PCNA was the poorest, with an AUC of 0.693 (95% CI: 0.645-0.741). The AUC of four candidate TAAbs in differentiating between HBV-HCC and HBV-LC patients ranged from 0.589 to 0.624. Among them, anti-PCNA had the most diagnostic capacity, with an AUC of 0.624 (95% CI: 0.569-0.679). Anti-CDC37L1 had the least diagnostic capability, with an AUC of 0.589 (95% CI: 0.533-0.645).
Supplementary Table S3 from Combination of an Autoantibody Panel and Alpha-Fetoprotein for Early Detection of Hepatitis B Virus-Associated Hepatocellular Carcinoma
Authors: Shen Yajing , Chen Jiajun , Wu Jinyu , Li Tiandong , Yi Chuncheng , Wang Keyan , Wang Peng , Sun Changqing , Ye Hua
Published: May 2024

Supplementary Table S3: Samples from the training set (116 HBV-HCC samples, 124 HBV-LC samples, and 157 CHB samples) were used to construct a predictive model and samples from the test set (78 HBV-HCC samples, 82 HBV-LC samples, and 106 CHB samples) were used to verify the stability of the model. The characteristics of samples in the training and test sets are shown in Supplementary Table S3.
Supplementary Figure S2 from Combination of an Autoantibody Panel and Alpha-Fetoprotein for Early Detection of Hepatitis B Virus-Associated Hepatocellular Carcinoma
Authors: Shen Yajing , Chen Jiajun , Wu Jinyu , Li Tiandong , Yi Chuncheng , Wang Keyan , Wang Peng , Sun Changqing , Ye Hua
Published: May 2024

Supplementary Figure S2: Samples (n=192) from GSE22058 were clustered and analyzed to detect the presence of outliers. Sample clustering demonstrated that two outliers (GSM548410 and GSM548460) need to be removed and the remaining samples (n=190) were applied for subsequent analyses (Supplementary Figure S2A). The scale-free modules were constructed by the optimal threshold of β=4 (Supplementary Figure S2B). Genes were divided into 16 modules by the thresholding power (Supplementary Figure S2C). The blue module had the highest correlation with the sample traits (r=0.93, P<0.001) (Supplementary Figure S2D) and the genes in this module were highly correlated with clinical information (cor=0.98, P<0.001) (Supplementary Figure S2E).
Supplementary Figure S1 from Combination of an Autoantibody Panel and Alpha-Fetoprotein for Early Detection of Hepatitis B Virus-Associated Hepatocellular Carcinoma
Authors: Shen Yajing , Chen Jiajun , Wu Jinyu , Li Tiandong , Yi Chuncheng , Wang Keyan , Wang Peng , Sun Changqing , Ye Hua
Published: May 2024

Supplementary Figure S1: In the discovery phase, a total of 71 differentially expressed TAAbs between the HCC and NC groups were identified using HuProt™ microarray (Supplementary Figure S1). These proteins could clearly distinguish the HCC group from the NC group.
Supplementary Table 6 from Triple Primary Cancers: An Analysis of Genetic and Environmental Factors
Authors: Borja Nicholas A. , Silva-Smith Rachel , Calfa Carmen , Sussman Daniel A. , Tekin Mustafa
Published: May 2024

Supplementary Table 6: Sensitivity analysis comparing treatment received for each cancer diagnosis, with the exclusion of all skin cancer cases.
Supplementary Table 4 from Triple Primary Cancers: An Analysis of Genetic and Environmental Factors
Authors: Borja Nicholas A. , Silva-Smith Rachel , Calfa Carmen , Sussman Daniel A. , Tekin Mustafa
Published: May 2024

Supplementary Table 4: Number of genes tested over time in the MPC patient cohort and its effect on hereditary cancer sequencing results
Supplementary Figure 1 from Triple Primary Cancers: An Analysis of Genetic and Environmental Factors
Authors: Borja Nicholas A. , Silva-Smith Rachel , Calfa Carmen , Sussman Daniel A. , Tekin Mustafa
Published: May 2024

Supplementary Figure 1: Flow diagram of patients evaluated with the selection criteria sequentially applied in order to define the triple primary cancer cohort for further analysis.
Effect of Clonal Hematopoiesis Mutations and Canakinumab Treatment on Incidence of Solid Tumors in the CANTOS Randomized Clinical Trial
Authors: Woo Janghee , Zhai Tingting , Yang Fang , Xu Huilei , Healey Margaret L. , Yates Denise P. , Beste Michael T. , Steensma David P.
Published: May 2024

Clonal hematopoiesis (CH) is more common in older persons and has been associated with an increased risk of hematological cancers and cardiovascular diseases. The most common CH mutations occur in the DNMT3A and TET2 genes and result in increased proinflammatory signaling. The Canakinumab Anti-inflammatory Thrombosis Outcome Study (NCT01327846) evaluated the neutralizing anti-IL1β antibody canakinumab in 10,061 randomized patients with a history of myocardial infarction and persistent inflammation; DNA samples were available from 3,923 patients for targeted genomic sequencing. We examined the incidence of non-hematological malignancy by treatment assignment and CH mutations and estimated the cumulative incidence of malignancy events during trial follow-up. Patients with TET2 mutations treated with canakinumab had the lowest incidence of non-hematological malignancy across cancer types. The cumulative incidence of at least one reported malignancy was lower for patients with TET2 mutations treated with canakinumab versus those treated with placebo. These findings support a potential role for canakinumab in cancer prevention and provide evidence of IL1β blockade cooperating with CH mutations to modify the disease course.

Prevention Relevance: We reveal that administering canakinumab is associated with a decrease in non-hematological malignancies among patients with clonal hematopoiesis (CH) mutations. These findings underscore canakinumab’s potential in preventing cancer and provide proof of IL1β blockade collaborating with CH mutations to enhance its clinical benefits.

See related Spotlight, p. 399
Figure S1, Figure S2, Figure S3, Figure S4 from Co-clinical Trial of Novel Bispecific Anti-HER2 Antibody Zanidatamab in Patient-Derived Xenografts
Authors: DiPeri Timothy P. , Evans Kurt W. , Wang Bailiang , Zhao Ming , Akcakanat Argun , Raso Maria Gabriela , Rizvi Yasmeen Q. , Zheng Xiaofeng , Korkut Anil , Varadarajan Kaushik , Uzunparmak Burak , Dumbrava Ecaterina E. , Pant Shubham , Ajani Jaffer A. , Pohlmann Paula R. , Jensen V. Behrana , Javle Milind , Rodon Jordi , Meric-Bernstam Funda
Published: May 2024

Supplementary Figure 1: HER2 status of patients and corresponding PDX models. HER2 expression was assessed by IHC and ERBB2 amplification status by FISH and NGS. FISH, fluorescence in situ hybridization; HER2, human epidermal growth factor receptor 2; NGS, next-generation sequencing. Alterations represents genomic alterations in available CLIA genomic testing on archival patient samples (matching PDX hosts). CLIA results were not available for patients matching PDX.003.025, PDX.003.263, and PDX.003.230.

Supplementary Figure 2: Actionable gene alterations in patient biopsies compared to the alteration in the resulting PDX as determined by whole exome sequencing on both.

Supplementary Figure 3: Cell viability assay with crizotinib. Cells were treated with crizotinib at serial dilutions for 72 hours. Following SRB staining, IC50 was calculated using CalcuSyn.

Supplementary Figure 4. In vivo assessment of zanidatamab in combination with BET inhibitor JQ1. 50 mg/kg JQ1 had no antitumor effects as single agent and did not add benefit when combined with 16 mg/kg zanidatamab.
Table S1 from PVRL2 Suppresses Antitumor Immunity through PVRIG- and TIGIT-independent Pathways
Authors: Yang Jiuling , Wang Li , Byrnes James R. , Kirkemo Lisa L. , Driks Hannah , Belair Cassandra D. , Aguilar Oscar A. , Lanier Lewis L. , Wells James A. , Fong Lawrence , Blelloch Robert
Published: May 2024

Supplementary Table S1: Statistical analysis comparing the areas under curves (AUC) of tumor growth data between groups using an unpaired Student’s t test.
Figure S2 from PVRL2 Suppresses Antitumor Immunity through PVRIG- and TIGIT-independent Pathways
Authors: Yang Jiuling , Wang Li , Byrnes James R. , Kirkemo Lisa L. , Driks Hannah , Belair Cassandra D. , Aguilar Oscar A. , Lanier Lewis L. , Wells James A. , Fong Lawrence , Blelloch Robert
Published: May 2024

Supplementary Figure S2: PVRL2 promotes tumor growth through an immune-dependent mechanism.
Figure S1 from PVRL2 Suppresses Antitumor Immunity through PVRIG- and TIGIT-independent Pathways
Authors: Yang Jiuling , Wang Li , Byrnes James R. , Kirkemo Lisa L. , Driks Hannah , Belair Cassandra D. , Aguilar Oscar A. , Lanier Lewis L. , Wells James A. , Fong Lawrence , Blelloch Robert
Published: May 2024

Supplementary Figure S1: Proteomic analysis identifies PVRL2 on tumor-derived exosomes.
Supplementary Tables 1-7 from High-Dimensional Analyses Reveal IL15 Enhances Activation of Sipuleucel-T Lymphocyte Subsets and Reverses Immunoresistance
Authors: Saeed Muhammad A. , Peng Bo , Kim Kevin , Rawat Kavita , Kuehm Lindsey M. , Siegel Zoe R. , Borkowski Ariel , Habib Nabih , Van Tine Brian , Sheikh Nadeem , Tuyen Vu , Thorek Daniel L.J. , Fehniger Todd A. , Pachynski Russell K.
Published: May 2024

Supplementary Tables 1-7
Supplementary Data from Tsyn-Seq: a T-cell Synapse–Based Antigen Identification Platform
Authors: Jin Yimei , Miyama Takahiko , Brown Alexandria , Hayase Tomo , Song Xingzhi , Singh Anand K. , Huang Licai , Flores Ivonne I. , McDaniel Lauren K. , Glover Israel , Halsey Taylor M. , Prasad Rishika , Chapa Valerie , Ahmed Saira , Zhang Jianhua , Rai Kunal , Peterson Christine B. , Lizee Gregory , Karmouch Jennifer , Hayase Eiko , Molldrem Jeffrey J. , Chang Chia-Chi , Tsai Wen-Bin , Jenq Robert R.
Published: May 2024

Supplementary Data
Figure S4 from Tsyn-Seq: a T-cell Synapse–Based Antigen Identification Platform
Authors: Jin Yimei , Miyama Takahiko , Brown Alexandria , Hayase Tomo , Song Xingzhi , Singh Anand K. , Huang Licai , Flores Ivonne I. , McDaniel Lauren K. , Glover Israel , Halsey Taylor M. , Prasad Rishika , Chapa Valerie , Ahmed Saira , Zhang Jianhua , Rai Kunal , Peterson Christine B. , Lizee Gregory , Karmouch Jennifer , Hayase Eiko , Molldrem Jeffrey J. , Chang Chia-Chi , Tsai Wen-Bin , Jenq Robert R.
Published: May 2024

Generation of reporter cells overexpressing CaSki cDNA library.
Figure S2 from Tsyn-Seq: a T-cell Synapse–Based Antigen Identification Platform
Authors: Jin Yimei , Miyama Takahiko , Brown Alexandria , Hayase Tomo , Song Xingzhi , Singh Anand K. , Huang Licai , Flores Ivonne I. , McDaniel Lauren K. , Glover Israel , Halsey Taylor M. , Prasad Rishika , Chapa Valerie , Ahmed Saira , Zhang Jianhua , Rai Kunal , Peterson Christine B. , Lizee Gregory , Karmouch Jennifer , Hayase Eiko , Molldrem Jeffrey J. , Chang Chia-Chi , Tsai Wen-Bin , Jenq Robert R.
Published: May 2024

Aggregates of interacting target cells and T cells.
Figure S1 from Tsyn-Seq: a T-cell Synapse–Based Antigen Identification Platform
Authors: Jin Yimei , Miyama Takahiko , Brown Alexandria , Hayase Tomo , Song Xingzhi , Singh Anand K. , Huang Licai , Flores Ivonne I. , McDaniel Lauren K. , Glover Israel , Halsey Taylor M. , Prasad Rishika , Chapa Valerie , Ahmed Saira , Zhang Jianhua , Rai Kunal , Peterson Christine B. , Lizee Gregory , Karmouch Jennifer , Hayase Eiko , Molldrem Jeffrey J. , Chang Chia-Chi , Tsai Wen-Bin , Jenq Robert R.
Published: May 2024

Activation of Fas-iNFκB reporter in FIR-APCs.
Supplementary Table S6 from Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer
Authors: Blise Katie E. , Sivagnanam Shamilene , Betts Courtney B. , Betre Konjit , Kirchberger Nell , Tate Benjamin J. , Furth Emma E. , Dias Costa Andressa , Nowak Jonathan A. , Wolpin Brian M. , Vonderheide Robert H. , Goecks Jeremy , Coussens Lisa M. , Byrne Katelyn T.
Published: May 2024

Supplementary Table S6. Quantification of Cell-Cell Spatial Interactions.
Figure S6 from ILT2 and ILT4 Drive Myeloid Suppression via Both Overlapping and Distinct Mechanisms
Authors: Tian Jane , Ashique Amir M. , Weeks Sabrina , Lan Tian , Yang Hong , Chen Hung-I Harry , Song Christina , Koyano Kikuye , Mondal Kalyani , Tsai Daniel , Cheung Isla , Moshrefi Mehrdad , Kekatpure Avantika , Fan Bin , Li Betty , Qurashi Samir , Rocha Lauren , Aguayo Jonathan , Rodgers Col , Meza Marchelle , Heeke Darren , Medfisch Sara M. , Chu Chun , Starck Shelley , Basak Nandini Pal , Sankaran Satish , Malhotra Mohit , Crawley Suzanne , Tran Thomas-Toan , Duey Dana Y. , Ho Carmence , Mikaelian Igor , Liu Wenhui , Rivera Lee B. , Huang Jiawei , Paavola Kevin J. , O'Hollaren Kyle , Blum Lisa K. , Lin Vicky Y. , Chen Peirong , Iyer Anjushree , He Sisi , Roda Julie M. , Wang Yan , Sissons James , Kutach Alan K. , Kaplan Daniel D. , Stone Geoffrey W.
Published: May 2024

Supplementary Figure S6
Supplementary Table S2 from Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer
Authors: Blise Katie E. , Sivagnanam Shamilene , Betts Courtney B. , Betre Konjit , Kirchberger Nell , Tate Benjamin J. , Furth Emma E. , Dias Costa Andressa , Nowak Jonathan A. , Wolpin Brian M. , Vonderheide Robert H. , Goecks Jeremy , Coussens Lisa M. , Byrne Katelyn T.
Published: May 2024

Supplementary Table S2. Tissue area sampled per patient out of total tissue area resected per
patient (in mm2).
Figure S3 from ILT2 and ILT4 Drive Myeloid Suppression via Both Overlapping and Distinct Mechanisms
Authors: Tian Jane , Ashique Amir M. , Weeks Sabrina , Lan Tian , Yang Hong , Chen Hung-I Harry , Song Christina , Koyano Kikuye , Mondal Kalyani , Tsai Daniel , Cheung Isla , Moshrefi Mehrdad , Kekatpure Avantika , Fan Bin , Li Betty , Qurashi Samir , Rocha Lauren , Aguayo Jonathan , Rodgers Col , Meza Marchelle , Heeke Darren , Medfisch Sara M. , Chu Chun , Starck Shelley , Basak Nandini Pal , Sankaran Satish , Malhotra Mohit , Crawley Suzanne , Tran Thomas-Toan , Duey Dana Y. , Ho Carmence , Mikaelian Igor , Liu Wenhui , Rivera Lee B. , Huang Jiawei , Paavola Kevin J. , O'Hollaren Kyle , Blum Lisa K. , Lin Vicky Y. , Chen Peirong , Iyer Anjushree , He Sisi , Roda Julie M. , Wang Yan , Sissons James , Kutach Alan K. , Kaplan Daniel D. , Stone Geoffrey W.
Published: May 2024

Supplementary Figure S3
Figure S16 from ILT2 and ILT4 Drive Myeloid Suppression via Both Overlapping and Distinct Mechanisms
Authors: Tian Jane , Ashique Amir M. , Weeks Sabrina , Lan Tian , Yang Hong , Chen Hung-I Harry , Song Christina , Koyano Kikuye , Mondal Kalyani , Tsai Daniel , Cheung Isla , Moshrefi Mehrdad , Kekatpure Avantika , Fan Bin , Li Betty , Qurashi Samir , Rocha Lauren , Aguayo Jonathan , Rodgers Col , Meza Marchelle , Heeke Darren , Medfisch Sara M. , Chu Chun , Starck Shelley , Basak Nandini Pal , Sankaran Satish , Malhotra Mohit , Crawley Suzanne , Tran Thomas-Toan , Duey Dana Y. , Ho Carmence , Mikaelian Igor , Liu Wenhui , Rivera Lee B. , Huang Jiawei , Paavola Kevin J. , O'Hollaren Kyle , Blum Lisa K. , Lin Vicky Y. , Chen Peirong , Iyer Anjushree , He Sisi , Roda Julie M. , Wang Yan , Sissons James , Kutach Alan K. , Kaplan Daniel D. , Stone Geoffrey W.
Published: May 2024

Supplementary Figure S16
Figure S15 from ILT2 and ILT4 Drive Myeloid Suppression via Both Overlapping and Distinct Mechanisms
Authors: Tian Jane , Ashique Amir M. , Weeks Sabrina , Lan Tian , Yang Hong , Chen Hung-I Harry , Song Christina , Koyano Kikuye , Mondal Kalyani , Tsai Daniel , Cheung Isla , Moshrefi Mehrdad , Kekatpure Avantika , Fan Bin , Li Betty , Qurashi Samir , Rocha Lauren , Aguayo Jonathan , Rodgers Col , Meza Marchelle , Heeke Darren , Medfisch Sara M. , Chu Chun , Starck Shelley , Basak Nandini Pal , Sankaran Satish , Malhotra Mohit , Crawley Suzanne , Tran Thomas-Toan , Duey Dana Y. , Ho Carmence , Mikaelian Igor , Liu Wenhui , Rivera Lee B. , Huang Jiawei , Paavola Kevin J. , O'Hollaren Kyle , Blum Lisa K. , Lin Vicky Y. , Chen Peirong , Iyer Anjushree , He Sisi , Roda Julie M. , Wang Yan , Sissons James , Kutach Alan K. , Kaplan Daniel D. , Stone Geoffrey W.
Published: May 2024

Supplementary Figure S15
Supplementary Figure S2 from Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer
Authors: Blise Katie E. , Sivagnanam Shamilene , Betts Courtney B. , Betre Konjit , Kirchberger Nell , Tate Benjamin J. , Furth Emma E. , Dias Costa Andressa , Nowak Jonathan A. , Wolpin Brian M. , Vonderheide Robert H. , Goecks Jeremy , Coussens Lisa M. , Byrne Katelyn T.
Published: May 2024

Supplementary Figure S2. A. SHAP plots showing the top 30 features driving each histopathologic model.
Features are ordered on the y-axis such that those with a larger impact on model’s predictions appear at the top
of the SHAP plots. SHAP values are shown on the x-axis, with a value of zero (center) indicating no impact on the model, and negative or positive SHAP values predicting
treatment-naive or αCD40-treated tissues, respectively. Red or blue dots indicate presence or absence,
respectively, of the corresponding feature in the tissue. B-E. Box plots showing feature values for each of the
top 15 features for models derived from T, IA, TAS, or NAP sites, respectively, split by treatment cohort. Each
dot represents the log10+1 normalized feature value for one tissue region, inputted into the classifier model.
Boxes = quartile 1 (Q1) to quartile 3 (Q3); whiskers = smallest and largest datapoints within 1.5*interquartile
range (IQR) +/- Q3/Q1; solid line = median. Mann–Whitney U-test used to determine statistical significance.
P-values corrected using the Benjamini–Hochberg procedure. *, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001. B. T site,
n= 55 treatment-naive and n = 48 αCD40-treated regions per feature. C. IA site, n= 89 treatment-naive and
n = 43 αCD40-treated regions per feature. D. TAS site, n = 25 treatment-naive and n = 27 αCD40-treated
regions per feature. E. NAP site, n = 6 treatment-naive and n = 13 αCD40-treated regions per feature.