Table 5 Final prioritization prompts and output, factoring in both fact-checked justification summaries and textualized transcriptome profiling data

PROMPT 1: Based on the summary below, please recommend the top candidate gene to include in a targeted blood transcriptional profiling panel. The intent is for the selected gene to be representative of an erythroid cell signature associated with response to mRNA vaccines, severity of RSV infection and that found to be expressed at high levels in patients with metastatic melanoma and in liver transplant recipients. Please weigh the following criteria equally in your recommendation: (1) Relevance to erythroid cells and erythropoiesis, (2) Current use as a biomarker, (3) Potential use as a blood transcriptional biomarker, (4) Relevance to leukocyte immune biology, (5) Status as a known drug target, (6) Therapeutic relevance for immune mediated diseases: [input summarized and fact-checked justifications from Step 5]

Based on the provided summary, I would recommend ALAS2 as the top candidate gene to include in the targeted blood transcriptional profiling panel. The key reasons are:

•ALAS2 plays a crucial and specific role in heme biosynthesis in erythroid cells, making it highly relevant to erythropoiesis. This aligns closely with the aim to select a gene representative of an erythroid signature

•While not yet an established biomarker, ALAS2 has potential utility as a blood transcriptional biomarker for conditions affecting heme biosynthesis like sideroblastic anemia, given its integral involvement

•ALAS2 is already an established therapeutic target for a condition affecting erythropoiesis and red blood cells—X-linked sideroblastic anemia. This demonstrates its translational relevance

•In contrast, the other genes have limitations regarding erythroid specificity (BCL2L1), lack of broad biomarker potential (CA1, FECH), unclear relevance as a drug target (SLC4A1), or less direct involvement in erythropoiesis (FECH)

In summary, ALAS2's crucial and specific role in heme biosynthesis in erythroid cells, translational relevance as a therapeutic target, and potential as a blood transcriptional biomarker make it the top choice to represent an erythroid signature for the intended profiling panel

Based on the provided summary, the most suitable candidate gene to include in the targeted blood transcriptional profiling panel, considering all the specified criteria, appears to be the BCL2L1 gene

1.Relevance to erythroid cells and erythropoiesis: While BCL2L1 does not have direct involvement in erythropoiesis, it plays a crucial role in cellular apoptosis regulation, which affects erythroid cells

2.Current use as a biomarker: Although not widely used, BCL2L1's role in apoptosis regulation can make it an interesting candidate for certain malignancies

3.Potential use as a blood transcriptional biomarker: BCL2L1 holds potential as a biomarker for diseases associated with apoptosis dysregulation, like certain cancers

4.Relevance to leukocyte immune biology: BCL2L1's function in apoptosis regulation is crucial to the lifespan and function of immune cells, making it highly relevant to leukocyte immune biology

5.Status as a known drug target: BCL2L1 is a significant target in cancer therapy, with strategies being developed to inhibit its anti-apoptotic function

6.Therapeutic relevance for immune-mediated diseases: BCL2L1, by regulating apoptosis in lymphocytes, holds potential therapeutic value for immune-mediated diseases

While the other genes also have their unique advantages and applications, the BCL2L1 gene is the most versatile across the provided criteria. It is important to note, however, that the utility and effectiveness of BCL2L1 as a representative of an erythroid cell signature will depend on the specific clinical and research contexts, and further research might be necessary to fully confirm its potential in this regard

PROMP 2: Now that you have provided an initial recommendation based on the summary, take into account the following RNA-sequencing expression data from key immune cell types and whole blood samples: [input textualized transcriptional data]. Given this additional RNA-seq expression data, does your recommended gene selection remain the same? Please explain which gene you would recommend at this stage and why, incorporating both the summarized information provided earlier and RNA-seq data in your rationale."

After reviewing the additional RNA-seq expression data, I would maintain my original recommendation of ALAS2 as the top candidate gene to include in the targeted blood transcriptional profiling panel

The key reasons are:

•The RNA-seq data confirms the erythroid-specific expression of ALAS2, with counts of 616 in whole blood but only 1 in all the leukocyte subsets. This aligns perfectly with the intent to select a gene representative of an erythroid signature

•In contrast, the other genes like BCL2L1, SLC4A1, CA1 and FECH exhibit low but detectable expression across leukocyte subsets, indicating they are more broadly expressed across blood cell types

•The erythroid-restricted expression of ALAS2 makes it a better biomarker of erythropoiesis compared to the other genes

•ALAS2 remains a relevant therapeutic target for disorders of erythropoiesis like sideroblastic anemia, despite the additional RNA-seq data

•The RNA-seq data does not provide any evidence to contradict ALAS2's integral role in heme biosynthesis in erythroid cells specifically

In summary, the RNA-seq data confirming erythroid-restricted expression of ALAS2 further strengthens the rationale for selecting it as the top candidate gene representative of an erythroid signature for the intended blood transcriptional profiling panel, in line with my original recommendation. The other genes appear more broadly expressed across leukocytes based on the RNA-seq data

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With the addition of the RNA-seq data, it's clear that ALAS2 is the most abundantly expressed gene in whole blood with a count of 616. This contrasts with BCL2L1, the initially recommended gene, which exhibits a lower expression level in whole blood (280). Importantly, ALAS2 demonstrates minimal expression in all other tested immune cells (counts of 1), suggesting a strong erythroid cell-specific expression, fitting the criteria to be representative of an erythroid cell signature. BCL2L1, on the other hand, is more uniformly expressed across various cell types, which makes it less specific to erythroid cells

Given these findings, I recommend reconsidering the selection and placing ALAS2 as the top candidate gene for inclusion in the targeted blood transcriptional profiling panel. Here's why:

1. Relevance to erythroid cells and erythropoiesis: ALAS2 plays an essential role in heme biosynthesis in red blood cells, a process critical for erythropoiesis

2. Current use as a biomarker: ALAS2 is used as a biomarker and therapeutic target for X-linked sideroblastic anemia

3. Potential use as a blood transcriptional biomarker: Although not typically utilized as a blood transcriptional biomarker, its high expression in whole blood and critical role in erythropoiesis highlight its potential

4. Relevance to leukocyte immune biology: Although it has limited relevance to circulating leukocyte immune biology due to its erythroid-specific nature, its low expression in other immune cells supports its specificity for erythroid cells

5. Status as a known drug target: ALAS2 has been targeted for the treatment of X-linked sideroblastic anemia

6. Therapeutic relevance for immune-mediated diseases: Although it has limited relevance for immune-mediated diseases, it can be relevant for immune-mediated hemolytic anemias

7. By combining both the RNA-seq data and the summary provided earlier, it appears that ALAS2 would be a more appropriate candidate due to its high expression in whole blood and its critical role in erythropoiesis, despite its limited involvement in leukocyte immune biology and use in immune-mediated diseases

PROMPT 3: Now that you have provided an initial recommendation based on the summary and the RNAseq data, take into account the following microarray expression data from key immune cell types and hematopoietic precursors: [input textualized transcriptional data]. Given this additional microarray expression data, does your recommended gene selection remain the same? Please explain which gene you would recommend at this stage and why, incorporating the summarized information and RNA-seq data provided earlier, as well as this new microarray data in your rationale

After reviewing the extensive microarray expression data, I would still recommend ALAS2 as the top candidate gene for inclusion in the targeted blood transcriptional profiling panel

The key reasons are:

•The microarray data confirms very high, erythroid-restricted expression of ALAS2 in the GlyA + erythroblast subsets, with values of 8371, 7664, and 5566 signal intensity units. This agrees with the RNA-seq data showing erythroid specificity

•ALAS2 expression is low (values < 100) in all immune cell types profiled by microarrays, including T cells, B cells, NK cells, dendritic cells. This further confirms leukocyte-restricted expression

•Other genes like BCL2L1, SLC4A1, CA1 and FECH are more broadly expressed across immune cells and progenitors, based on the microarray data

•No additional insight from the microarrays contradicts ALAS2's integral involvement in heme biosynthesis in erythroid lineage cells specifically

•ALAS2 remains a relevant therapeutic target in erythroid disorders based on its key role, despite the new microarray data

In summary, the extensive microarray expression profiling continues to support ALAS2 as the top gene choice representative of an erythroid signature, based on its high erythroid-restricted expression and lack of expression in other immune cells. The other genes appear more broadly expressed across leukocytes. Therefore, I maintain ALAS2 as my recommended top candidate gene for inclusion in the intended targeted blood transcriptional profiling panel

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[N/A: input exceed GPT-4 limits. Attempts to break down inputting the textualized data were unsuccessful as GPT-4 lost the thread of the conversation. Thus, we chose to skip to the next prompt]

PROMPT 4: Now that you have provided an initial recommendation based on the summary and the immune cells RNAseq and microarray data, take into account the following averaged log2 fold changes in RNA abundance in patient cohorts compared to controls. [input textualized transcriptional data]. Given this additional data, does your recommended gene selection remain the same? Please explain which gene you would recommend at this stage and why, incorporating the summarized information, the leukocytes RNA-seq and microarray data provided earlier, as well as these new patient cohort profiles in your rationale

After reviewing the log2 fold change data across multiple patient cohorts, I would maintain my recommendation of ALAS2 as the top candidate gene for the intended blood transcriptional profiling panel

The key reasons are:

• ALAS2 shows some of the largest fold changes across conditions like RSV infection, metastatic melanoma, and juvenile arthritis that were called out in the original summary as being relevant

• The magnitude of ALAS2 fold changes are greater than those seen for other genes like BCL2L1, SLC4A1, CA1 and FECH in many of the disease states

• ALAS2's erythroid-specific expression makes its fold changes more amenable to interpretation compared to broadly expressed genes

• No major contradictory evidence arises from the fold change data to refute ALAS2's important role in erythropoiesis

• The leukocyte expression data and key role in heme synthesis remain valid points strengthening ALAS2's selection despite the new cohort profiles

In summary, the gene expression fold changes across multiple patient cohorts and conditions continues to support ALAS2 as a top gene choice representative of an erythroid signature that could provide insights into disease biology based on its marked regulation. The other genes do not show as large or as consistent differences across relevant conditions based on the log2 fold change data. Therefore, I maintain ALAS2 as my recommended top candidate gene for the intended blood profiling panel

[GPT-4 was able to interpret the input transcriptional data but lost the thread of the conversation]

In the analysis, we observed differences in RNA abundance in whole blood for BCL2L1, ALAS2, SLC4A1, CA1, and FECH across various patient groups compared to controls. Let's summarize some of the notable findings:

1.BCL2L1: BCL2L1 expression seems to increase in cases of B-cell deficiency, metastatic melanoma, sepsis, pregnancy, active pulmonary tuberculosis, acute respiratory syncytial virus infection, systemic onset juvenile idiopathic arthritis, staphylococcus aureus infection, and liver transplant recipients. The most pronounced increase was observed in patients with metastatic melanoma. On the other hand, its expression decreases in patients with diseases like chronic obstructive pulmonary disease (COPD), acute influenza, HIV, juvenile dermatomyositis, Kawasaki disease, and multiple sclerosis. The most substantial decrease was observed in patients with HIV infection

2.ALAS2: ALAS2 expression increased in patients with B-cell deficiency, Kawasaki disease, metastatic melanoma, sepsis, pregnancy, active pulmonary tuberculosis, acute respiratory syncytial virus infection, systemic onset juvenile idiopathic arthritis, staphylococcus aureus infection, and liver transplant recipients. The most pronounced increase was seen in patients with metastatic melanoma. However, its expression decreased in patients with COPD, acute influenza, HIV, and juvenile dermatomyositis. The greatest decrease was observed in HIV infection

3.SLC4A1: SLC4A1 expression increased in patients with Kawasaki disease, metastatic melanoma, sepsis, pregnancy, active pulmonary tuberculosis, acute respiratory syncytial virus infection, staphylococcus aureus infection, and liver transplant recipients, with metastatic melanoma showing the highest increase. On the other hand, it decreased in patients with B-cell deficiency, COPD, acute influenza, HIV, juvenile dermatomyositis, and multiple sclerosis. The greatest decrease was observed in patients with HIV infection

4.CA1: CA1 expression increased dramatically in most conditions, especially metastatic melanoma, sepsis, pregnancy, active pulmonary tuberculosis, acute respiratory syncytial virus infection, systemic lupus erythematosus, systemic onset juvenile idiopathic arthritis, staphylococcus aureus infection, and liver transplant recipients. The greatest increase was observed in sepsis patients. However, it decreased in patients with B-cell deficiency, COPD, acute influenza, HIV, and multiple sclerosis. The most significant decrease was seen in HIV patients

5.FECH: FECH expression increased slightly in patients with B-cell deficiency and decreased slightly in patients with COPD, but the changes were less pronounced compared to other genes. The expression decreased in conditions like acute influenza, HIV, and juvenile dermatomyositis, with the most significant decrease observed in patients with HIV

In all cases, these changes in gene expression may represent physiological responses to disease or might contribute to the pathophysiology of the disease itself. These findings could be valuable for designing further research, or potentially, diagnostic or therapeutic strategies

Please note that the interpretation of gene expression data is complex, with many factors influencing the results, such as patient characteristics, sample handling, and microarray technique variability. Hence, these interpretations should be considered as hypotheses that need further validation

PROMPT 5: Could you please summarize the key conclusions you have drawn from the conversation so far?

Based on reviewing the initial summary, RNA-seq data, microarray data, and patient cohort fold change data provided sequentially, my conclusions are:

• I would recommend ALAS2 as the top candidate gene for inclusion in the intended targeted blood transcriptional profiling panel based on its:

1.Crucial, erythroid-specific role in heme biosynthesis, making it a good representation of an erythroid signature

2.Lack of expression in leukocytes and high, restricted expression in erythroblast subsets, confirmed by both RNA-seq and microarrays

3.Large, consistent fold changes across conditions like RSV infection, juvenile arthritis, and melanoma that were highlighted as being relevant

4.Established utility as a therapeutic target in erythroid disorders like sideroblastic anemia

5.Potential as a biomarker for disrupted erythropoiesis based on its tight regulation

• The other genes (BCL2L1, SLC4A1, CA1, FECH) are more broadly expressed across immune cells and their fold changes are smaller in magnitude or less consistent across key disease states

• Each additional dataset provided further evidence supporting ALAS2 as the top choice over other candidates based on erythroid specificity and associations with conditions of interest

In summary, the collective evidence strongly supports ALAS2 as the top gene for inclusion in the intended blood profiling panel to represent an erythroid signature. The key factors are its erythroid-restricted expression and marked regulation across relevant conditions

[N/A: GPT-4 could not keep the thread of the conversation following the input of large amount of textualized transcriptional profiling data]