Functional Effects of Four or Fewer Critical Genes Linked to Lung Cancers and New Subtypes Detected by A New Machine Learning Classifier

Zhang, Zhengjun

doi:10.1101/2021.10.08.463736

Cited by 18 publications

(76 citation statements)

References 22 publications

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“…However, (3) remains the desired properties of interpretability, computability, predictability, and stability. Note that this remark is the same as Remark 1 15 .…”

Section: Introductionmentioning

confidence: 69%

“…The following Proposition 2.1 mathematically guarantees the existence of desired solutions. The proof follows the lines in the work 15 by extending K = 1 to K = 2. Proposition 2.1.…”

Section: Methodsmentioning

confidence: 79%

“…Remark 3. The case of K = 1 corresponds to the classifier introduced in Zhang (2021) 15 . The case of K = 1 and λ 2 = 0 corresponds to the classifier introduced in Zhang (2021) 2 .…”

Section: Methodsmentioning

confidence: 99%

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The Existence of At Least Three Genomic Signature Patterns and At Least Seven Subtypes of COVID-19 and the End of the Disease

Zhang¹

2022

Preprint

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Hoping to find genomic clues linked to COVID-19 and end the pandemic has driven scientists' tremendous efforts to try all kinds of research. Signs of progress have been achieved but are still limited. This paper intends to prove the existence of at least three genomic signature patterns and at least seven subtypes of COVID-19 driven by five critical genes (the smallest subset of genes). These signatures and subtypes provide crucial genomic information in COVID-19 diagnosis (including ICU patients), research focuses, and treatment methods. Unlike existing approaches focused on gene fold-changes and pathways, gene-gene nonlinear and competing interactions are the driving forces in finding the signature patterns and subtypes. Furthermore, the method leads to 100\% accuracy, which shows biological and mathematical equivalences between COVID-19 status and the signature patterns and a methodological advantage over other existing methods that cannot lead to 100\% accuracy. As a result, as new biomarkers, the new findings can be much more informative than other findings for interpreting biological mechanisms, developing the second (third) generation of vaccines, antiviral drugs, and treatment methods, and eventually bringing new hopes to an end of the pandemic.

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“…However, (3) remains the desired properties of interpretability, computability, predictability, and stability. Note that this remark is the same as Remark 1 15 .…”

Section: Introductionmentioning

confidence: 69%

“…The following Proposition 2.1 mathematically guarantees the existence of desired solutions. The proof follows the lines in the work 15 by extending K = 1 to K = 2. Proposition 2.1.…”

Section: Methodsmentioning

confidence: 79%

See 1 more Smart Citation

The Existence of At Least Three Genomic Signature Patterns and At Least Seven Subtypes of COVID-19 and the End of the Disease

Zhang¹

2022

Preprint

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“…Finally, the complete computing description is listed in Zhang 21 in which 5 Covid-19 critical genes and 7 subtypes were identified, and the validity of (3) is shown theoretically in Zhang. 24 …”

Section: Statistical Methodologymentioning

confidence: 99%

Lift the Veil of Breast Cancers Using 4 or Fewer Critical Genes

Zhang

2022

Cancer Inform

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Known genes in the breast cancer study literature could not be confirmed whether they are vital to breast cancer formations due to lack of convincing accuracy, although they may be biologically directly related to breast cancer based on present biological knowledge. It is hoped vital genes can be identified with the highest possible accuracy, for example, 100% accuracy and convincing causal patterns beyond what has been known in breast cancer. One hope is that finding gene-gene interaction signatures and functional effects may solve the puzzle. This research uses a recently developed competing linear factor analysis method in differentially expressed gene detection to advance the study of breast cancer formation. Surprisingly, 3 genes are detected to be differentially expressed in TNBC and non-TNBC (Her2, Luminal A, Luminal B) samples with 100% sensitivity and 100% specificity in 1 study of triple-negative breast cancers (TNBC, with 54 675 genes and 265 samples). These 3 genes show a clear signature pattern of how TNBC patients can be grouped. For another TNBC study (with 54 673 genes and 66 samples), 4 genes bring the same accuracy of 100% sensitivity and 100% specificity. Four genes are found to have the same accuracy of 100% sensitivity and 100% specificity in 1 breast cancer study (with 54 675 genes and 121 samples), and the same 4 genes bring an accuracy of 100% sensitivity and 96.5% specificity in the fourth breast cancer study (with 60 483 genes and 1217 samples). These results show the 4-gene-based classifiers are robust and accurate. The detected genes naturally classify patients into subtypes, for example, 7 subtypes. These findings demonstrate the clearest gene-gene interaction patterns and functional effects with the smallest numbers of genes and the highest accuracy compared with findings reported in the literature. The 4 genes are considered to be essential for breast cancer studies and practice. They can provide focused, targeted researches and precision medicine for each subtype of breast cancer. New breast cancer disease types may be detected using the classified subtypes, and hence new effective therapies can be developed.

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“…Remark 3. The case of K = 1 corresponds to the classifier introduced in Zhang (2021) 20 . The case of K = 1 and λ 2 = 0 corresponds to the classifier introduced in Zhang (2021) 15 .…”

Section: Methodsmentioning

confidence: 99%

Genomic Biomarker Heterogeneities Between SARS-CoV-2 and COVID-19

Zhang¹

2022

Preprint

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Genes functionally associated with SARS-CoV-2 and genes functionally related to COVID-19 disease can be different, whose distinction will become the first essential step for successfully fighting against the COVID-19 pandemic. Unfortunately, this first step has not been completed in all biological and medical research. Using a newly developed max-competing logistic classifier, two genes, ATP6V1B2 and IFI27, stand out to be critical in transcriptional response to SARS-CoV-2 with differential expressions derived from NP/OP swab PCR. This finding is evidenced by combining these two genes with one another gene in predicting disease status to achieve better-indicating power than existing classifiers with the same number of genes. In addition, combining these two genes with three other genes to form a five-gene classifier outperforms existing classifiers with ten or more genes. With their exceptional predicting power, these two genes can be critical in fighting against the COVID-19 pandemic as a new focus and direction. Comparing the functional effects of these genes with a five-gene classifier with 100% accuracy identified and tested from blood samples in the literature, genes and their transcriptional response and functional effects to SARS-CoV-2 and genes and their functional signature patterns to COVID-19 antibody are significantly different, which can be interpreted as the former is the point of a phenomenon, and the latter is the essence of the disease. Such significant findings can help explore the causal and pathological clue between SARS-CoV-2 and COVID-19 disease and fight against the disease with more targeted vaccines, antiviral drugs, and therapies.

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Functional Effects of Four or Fewer Critical Genes Linked to Lung Cancers and New Subtypes Detected by A New Machine Learning Classifier

Cited by 18 publications

References 22 publications

The Existence of At Least Three Genomic Signature Patterns and At Least Seven Subtypes of COVID-19 and the End of the Disease

The Existence of At Least Three Genomic Signature Patterns and At Least Seven Subtypes of COVID-19 and the End of the Disease

Lift the Veil of Breast Cancers Using 4 or Fewer Critical Genes

Genomic Biomarker Heterogeneities Between SARS-CoV-2 and COVID-19

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