Jorge Blando

11.8k total citations · 2 hit papers
61 papers, 2.9k citations indexed

About

Jorge Blando is a scholar working on Oncology, Immunology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Jorge Blando has authored 61 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Oncology, 19 papers in Immunology and 17 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Jorge Blando's work include Cancer Immunotherapy and Biomarkers (34 papers), Immunotherapy and Immune Responses (10 papers) and Bladder and Urothelial Cancer Treatments (9 papers). Jorge Blando is often cited by papers focused on Cancer Immunotherapy and Biomarkers (34 papers), Immunotherapy and Immune Responses (10 papers) and Bladder and Urothelial Cancer Treatments (9 papers). Jorge Blando collaborates with scholars based in United States, Japan and United Kingdom. Jorge Blando's co-authors include Padmanee Sharma, James P. Allison, Luis M. Vence, Sumit K. Subudhi, John DiGiovanni, Jennifer A. Wargo, Hao Zhao, Jianjun Gao, Achinto Saha and Fernando Benavides and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Medicine.

In The Last Decade

Jorge Blando

61 papers receiving 2.8k citations

Hit Papers

VISTA is an inhibitory immune checkpoint that is increase... 2017 2026 2020 2023 2017 2018 100 200 300 400

Peers

Jorge Blando
Vasiliki Pelekanou United States
Seung-Oe Lim United States
Julienne L. Carstens United States
Fei Zhou China
Vijaya Ramachandran United States
Lanxi Song United States
Vasiliki Pelekanou United States
Jorge Blando
Citations per year, relative to Jorge Blando Jorge Blando (= 1×) peers Vasiliki Pelekanou

Countries citing papers authored by Jorge Blando

Since Specialization
Citations

This map shows the geographic impact of Jorge Blando's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jorge Blando with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jorge Blando more than expected).

Fields of papers citing papers by Jorge Blando

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jorge Blando. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jorge Blando. The network helps show where Jorge Blando may publish in the future.

Co-authorship network of co-authors of Jorge Blando

This figure shows the co-authorship network connecting the top 25 collaborators of Jorge Blando. A scholar is included among the top collaborators of Jorge Blando based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jorge Blando. Jorge Blando is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Poudel, Pawan, Emily C. Jennings, Felicia Ng, et al.. (2024). Exploring the impact of tertiary lymphoid structures maturity in NSCLC: insights from TLS scoring. Frontiers in Immunology. 15. 1422206–1422206. 2 indexed citations
2.
Goswami, Sangeeta, Yulong Chen, Swetha Anandhan, et al.. (2020). ARID1A mutation plus CXCL13 expression act as combinatorial biomarkers to predict responses to immune checkpoint therapy in mUCC. Science Translational Medicine. 12(548). 92 indexed citations
3.
Subudhi, Sumit K., Luis M. Vence, Hao Zhao, et al.. (2020). Neoantigen responses, immune correlates, and favorable outcomes after ipilimumab treatment of patients with prostate cancer. Science Translational Medicine. 12(537). 116 indexed citations
4.
Shi, Lewis Z., Sangeeta Goswami, Tihui Fu, et al.. (2019). Blockade of CTLA-4 and PD-1 Enhances Adoptive T-cell Therapy Efficacy in an ICOS-Mediated Manner. Cancer Immunology Research. 7(11). 1803–1812. 35 indexed citations
5.
Vence, Luis M., Samantha Bucktrout, Irina Fernandez Curbelo, et al.. (2019). Characterization and Comparison of GITR Expression in Solid Tumors. Clinical Cancer Research. 25(21). 6501–6510. 38 indexed citations
6.
Goswami, Sangeeta, Thomas Walle, Andrew Cornish, et al.. (2019). Immune profiling of human tumors identifies CD73 as a combinatorial target in glioblastoma. Nature Medicine. 26(1). 39–46. 251 indexed citations
7.
Nusrat, Maliha, Jason Roszik, Riham Katkhuda, et al.. (2019). Association of PIK3CA mutations (mut) with immune engagement and clinical benefit from immunotherapy in microsatellite stable (MSS) colorectal cancer (CRC) patients (pts).. Journal of Clinical Oncology. 37(15_suppl). 3604–3604. 13 indexed citations
8.
Sharma, Anu, Sumit K. Subudhi, Jorge Blando, et al.. (2018). Anti-CTLA-4 Immunotherapy Does Not Deplete FOXP3+ Regulatory T Cells (Tregs) in Human Cancers. Clinical Cancer Research. 25(4). 1233–1238. 266 indexed citations breakdown →
9.
Garg, Rachana, Jorge Blando, Carlos J. Pérez, et al.. (2018). COX-2 mediates pro-tumorigenic effects of PKCε in prostate cancer. Oncogene. 37(34). 4735–4749. 50 indexed citations
10.
Saha, Achinto, et al.. (2017). Proinflammatory CXCL12–CXCR4/CXCR7 Signaling Axis Drives Myc-Induced Prostate Cancer in Obese Mice. Cancer Research. 77(18). 5158–5168. 78 indexed citations
11.
Parra, Edwin R., Carmen Behrens, Jaime Rodriguez‐Canales, et al.. (2016). Image Analysis–based Assessment of PD-L1 and Tumor-Associated Immune Cells Density Supports Distinct Intratumoral Microenvironment Groups in Non–small Cell Lung Carcinoma Patients. Clinical Cancer Research. 22(24). 6278–6289. 103 indexed citations
12.
Shi, Lewis Z., Tihui Fu, Baoxiang Guan, et al.. (2016). Interdependent IL-7 and IFN-γ signalling in T-cell controls tumour eradication by combined α-CTLA-4+α-PD-1 therapy. Nature Communications. 7(1). 12335–12335. 81 indexed citations
13.
Saha, Achinto, et al.. (2015). Effect of Metformin, Rapamycin, and Their Combination on Growth and Progression of Prostate Tumors in HiMyc Mice. Cancer Prevention Research. 8(7). 597–606. 35 indexed citations
14.
Saha, Achinto, et al.. (2014). 6-Shogaol from Dried Ginger Inhibits Growth of Prostate Cancer Cells Both In Vitro and In Vivo through Inhibition of STAT3 and NF-κB Signaling. Cancer Prevention Research. 7(6). 627–638. 116 indexed citations
15.
Rho, Okkyung, Joe M. Angel, Jorge Blando, et al.. (2013). Metformin Inhibits Skin Tumor Promotion in Overweight and Obese Mice. Cancer Prevention Research. 7(1). 54–64. 44 indexed citations
16.
Yang, Guang, Alexei A. Goltsov, Chengzhen Ren, et al.. (2011). Caveolin-1 Upregulation Contributes to c-Myc–Induced High-Grade Prostatic Intraepithelial Neoplasia and Prostate Cancer. Molecular Cancer Research. 10(2). 218–229. 41 indexed citations
17.
Blando, Jorge, Tricia Moore, Stephen D. Hursting, et al.. (2011). Dietary Energy Balance Modulates Prostate Cancer Progression in Hi-Myc Mice. Cancer Prevention Research. 4(12). 2002–2014. 60 indexed citations
18.
Blando, Jorge, Steve Carbajal, Erika L. Abel, et al.. (2011). Cooperation between Stat3 and Akt Signaling Leads to Prostate Tumor Development in Transgenic Mice. Neoplasia. 13(3). 254–IN12. 35 indexed citations
19.
Benavides, Fernando, Jorge Blando, Carlos J. Pérez, et al.. (2011). Transgenic overexpression of PKCε in the mouse prostate induces preneoplastic lesions. Cell Cycle. 10(2). 268–277. 46 indexed citations
20.
Rojas, Paola, Fernando Benavides, Jorge Blando, et al.. (2008). Enhanced skin carcinogenesis and lack of thymus hyperplasia in transgenic mice expressing human cyclin D1b (CCND1b). Molecular Carcinogenesis. 48(6). 508–516. 8 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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